Knowledge Discovery 26.3.0
26.3 Release Notes

# Media Server

Media Server is an ACI server. For details of changes that affect all ACI servers, see ACI Server Framework.

## 26.3.0

### New Features

- Speech-to-text has a new model that offers an extraordinary improvement in performance. The new model provides equivalent accuracy to the `Large` model, but is significantly faster than `Medium`. When running on a GPU, the new model is faster than `Micro`.

  When running on a CPU, the new model can process audio in approximately 1.8 times the source duration (compared to >5 times for the `Large` model in earlier versions). The new model consumes approximately 13 GB of memory (compared to >25 GB for the `Large` model in earlier versions).

  TIP: These figures are based on one example system and are intended only as a guide. OpenText recommends running performance tests on your own system(s).

  The new model is named `Large`. The models previously named `Medium` and `Large` are no longer available. OpenText recommends that if you configure `ModelVersion=Medium`, you change your session configurations such that `ModelVersion=Large`. The value `Medium` is deprecated and might be removed in a future release. Until then, setting `ModelVersion=Medium` uses the same (new) model as `ModelVersion=Large`.

- Optical Character Recognition supports the following additional languages:

  - Latin alphabet - Azerbaijani (az), Indonesian (id), Malay (ms), Uzbek (uz)
  - Cyrillic alphabet - Kazakh (kk), Mongolian (mn), Tajik (tg)
  - Armenian (hy), Georgian (ka)

- Automatic Number Plate Recognition (ANPR) supports the following additional locations: Egypt (EG), Jordan (JO), Sudan (SD), and Yemen (YE).

### Resolved Issues

- Media Server could terminate unexpectedly if a large number of `process` actions ran at the same time.
- (Security update) The third-party FFmpeg library was updated to version 7.1.4.
- (Security update) The third-party libde265 library was updated to version 1.0.18.
- (Security update) The third-party zxing-cpp library was updated to version 3.0.2.
- (Security update) The third-party OpenCV library was updated to version 4.13.0.
- (Security update) The third-party libpng library was updated to version 1.6.58.
- (Security update) The third-party libaom library was updated to version 3.14.0.
- (Security update) The third-party thrift library was updated to version 0.23.0.
- (Security update) The third-party openjpeg library, version 2.5.4, has been patched to resolve CVE-2026-6192.

### Notes

- In the `[Modules]` section of the configuration file, the `Enable` parameter lists the modules to enable when Media Server starts. The value `Barcode` is now deprecated. In Media Server 26.3 and later, this module is always enabled.

## 26.2.0

### New Features

- Media Server 25.3 and later use the Torch machine learning library, instead of Caffe. This was a major architectural change and object class recognition training was disabled in versions 25.3 to 26.1. Object class recognition training is now supported and you can train recognizers using the action `BuildObjectClassRecognizer`.
- Media Server has a new analysis engine (`Type=ImageDescription`) which uses a Large Language Model (LLM) to generate textual descriptions of images and video frames. A single pre-trained model is available. This engine uses a significant amount of memory and when running on a CPU can take nine or ten minutes to process a single image. OpenText recommends running on a GPU, in which case images can be processed in approximately five seconds.
- Speech-to-text supports a new language, Finnish (`LanguagePack=FIFI`).
- Media Server includes new XSL templates for transforming OCR records to HTML (`toHTML_OCR.xsl`) and Markdown (`toMD_OCR.xsl`). Converting OCR output into Markdown can be useful when you want to send the text to a large language model (LLM).
- Visual clustering supports images and documents. In earlier versions of Media Server, visual clustering supported only videos.
- The Count engine can be used when the source media is an image or document. In earlier versions of Media Server, this engine supported only video.
- The values of the parameters `AllowedInputDirectories` and `AllowedEngineOutputDirectories` are now case-insensitive on Windows (where the underlying file system is case-insensitive). The values remain case-sensitive for Linux.

### Resolved Issues

- (Security update) The third-party libheif library was updated to version 1.21.1.
- (Security update) The third-party libpng library was updated to version 1.6.55.

### Notes

- Media Server 26.1 supports two object class recognizer types, named `small` and `large`. If you trained recognizers in an earlier version of Media Server and upgraded the models so that they are compatible with Torch (see "Upgrade Trained Models" in the Media Server Help), you will see the following:

  - `generation2` models become "large" recognizers and no further action is necessary.

  - `generation3` models become "small" recognizers and no further action is necessary.

  - `generation4` models can be used for analysis, but if you want to change the training you must run `SetObjectClassRecognizerTrainingOption` and choose either "small" or "large" before you run `BuildObjectClassRecognizer`.

- In the OCR analysis engine, the `KeepOnly` configuration parameter has been deprecated. OpenText recommends using the `WordRejectThreshold` parameter to specify a minimum confidence level for OCR output.
- In the MPEG encoding engine, the `MIMEType` configuration parameter has been deprecated. Media Server can determine the correct MIME type from the value of the `Format` or `OutputPath` parameter.
- The XSL template `toHTML_OCR.xsl` replaces `toHTMLTable.xsl`. The new template transforms all OCR output, whereas the former ignored text that was not part of a table.

## 26.1.0

### New Features

- The rotate transformation engine can rotate images by any number of degrees (earlier versions permitted only 90-degree increments). If you rotate an image and the rotation is not divisible by 90 degrees, Media Server adds padding and the resulting image will be larger than the original.

### Resolved Issues

There were no resolved issues in this release.

### Notes

- To enhance security, Media Server can no longer read from or write to any location in the local file system by default. You might need to set the parameters `AllowedInputDirectories` and `AllowedEngineOutputDirectories` in your Media Server configuration file, to specify the directories that Media Server can use.

## 25.4.0

### New Features

- The audio categorization analysis engine produces a new output track named `ResultWithAudio`. You can use this track as the input for speech-to-text, which will ignore any audio segments that are not labeled as speech. Running audio categorization followed by speech-to-text can improve performance when the input audio contains time periods (of more than a few seconds) without speech.
- Improved OCR accuracy, especially for numeric expressions in Arabic.

### Resolved Issues

- Face detection, speech-to-text, and training for image classification were slower on GPU in Media Server 25.3 than in Media Server 25.2. Performance has now been improved to match or exceed 25.2.

### Notes

- Legacy speech-to-text (`ModelVersion=Legacy`) has been removed from Media Server. OpenText recommends using the newer speech-to-text models introduced in Media Server 23.2. The newer models offer significantly better accuracy, especially for English speech.

## 25.3.0

IMPORTANT: In this release the action `BuildObjectClassRecognizer` is not available. This issue will be resolved in a future patch release.

### New Features

- Media Server uses the Torch machine learning library, instead of Caffe. This is a major architectural change that improves the speed of training and analysis, while at the same time reducing memory use. The amount of improvement varies by the type of analysis - for example face detection and recognition, object class recognition, and speech-to-text all show large improvements when running on CPU.
- Media Server supports CUDA version 12, providing support for a new generation of GPUs. CUDA versions 10 and 11 are no longer supported.
- Media Server can use more than one GPU. In earlier versions of Media Server, the `GPUDeviceID` parameter (in the `[Server]` section of the configuration file) specified the GPU to use for all training actions and analysis tasks. You can now set `GPUDeviceID` in training actions and analysis tasks that support use of a GPU, so that different tasks can run on different graphics cards. You can also set `GPUDeviceID=CPU`, to run a specific task on the CPU instead. While a single processing session can now use multiple GPUs, it is not possible to split a single analysis task across multiple GPUs.

### Resolved Issues

- (Security update) The third-party libheif library was updated to version 1.19.8.
- (Security update) The third-party libde265 library was updated to version 1.0.16.
- (Security update) The third-party aom library was updated to version 3.12.1.
- When a database of vehicle model training images was exported, the number plate locations were omitted. As a result, the `anprlocation` field was not populated correctly when the database was imported.

### Notes

- The replacement of Caffe with Torch is a major architectural change. Caffe and Torch models are not compatible, so before using Media Server 25.3, you must either retrain Media Server or convert your trained models. Converting trained models is much faster, and Media Server 25.3 includes tools to convert trained models so that they are compatible with Torch, but you will need a Python installation. For information about how to upgrade your models, refer to the Media Server Administration Guide.

  IMPORTANT: OpenText recommends that you make a backup of your database before beginning the upgrade.

- When you start Media Server, the `libs/torch` directory must be on the `PATH` (Windows) or `LD_LIBRARY_PATH` (Linux). OpenText recommends installing Media Server as a service. On Linux `LD_LIBRARY_PATH` is set by the service configuration or start script automatically, so if you install Media Server as a service no further action is required. On Windows, set the `PATH` environment variable for the user that runs the Media Server service, such that it includes the `libs\torch` directory. A new script, `start-mediaserver.bat`, is provided in case you want to start Media Server from the command-line on Windows.
- Object class recognition no longer supports `generation1` recognizers. If your database contains `generation1` recognizers you must re-train Media Server by running the action `UnsetObjectClassRecognizerTrainingOption` (to remove the `recognizer_type` option) followed by `BuildObjectClassRecognizer`. The default `recognizer_type` is now `generation4`.
- Speaker ID uses a new neural network, so after upgrading to Media Server 25.3 you must run the action `BuildAllSpeakers` to retrain Media Server.
- The `CUDAVersion` configuration parameter has been removed and no longer has any effect.
- Media Server places new restrictions on the characters that can be used in database names, classifier names, identifiers, labels, and metadata. Forbidden XML characters (including Unicode noncharacters) are not permitted in new names in Media Server 25.3 and later.

## 25.2.0

### New Features

- Image classification uses a new algorithm that provides better accuracy and shorter processing times. Classification is faster than earlier versions of Media Server when running on a GPU, and is much faster than earlier versions when running on a CPU. These improvements also result in better performance for vehicle make analysis and person analysis, which use image classification internally.
- OCR supports word-level output from text elements. Text that was extracted from a text element by File Content Extraction now appears in the `WordData` and `WordResult` output tracks.
- OCR is faster due to algorithm improvements and use of AVX-512 extensions (if supported by your server's CPU).

### Resolved Issues

There were no resolved issues in this release.

### Notes

- As a result of the changes to image classification, you must retrain your classifiers. Run `action=BuildClassifier` for each of your classifiers. If you are using one of the pre-trained classifiers provided by OpenText, download and import the latest version of the classifier.
- The deprecated OCR parameters `Blacklist` and `Whitelist` have been removed. Use the parameters `DisabledCharacters` and `ExtraEnabledCharacters` instead.
- The deprecated face detection macros and Lua table entries named `outofplaneanglex`, `outofplaneangley`, and `percentageinimage` have been removed. Use `outOfPlaneAngleX`, `outOfPlaneAngleY`, and `percentageInImage` instead (note the difference in case).
- The deprecated `SampleFrequency` parameter has been removed from speech-to-text and from the `AlignAudioTranscript` action. Media Server can determine the correct sample frequency from the language pack.
- The deprecated `startTime`, `duration`, and `endTime` fields have been removed from the output of the `AlignAudioTranscript` action. Use the `timestamp` field that provides timestamp information in both ISO 8601 format and in epoch microseconds.

## 25.1.0

### New Features

- (Security update) To strengthen security, you can restrict the file system paths that Media Server is permitted to read from. There is a new parameter named `AllowedInputDirectories`, in the `[Paths]` section of the configuration file. OpenText recommends that you set a value for this parameter. The default value allows Media Server to read files from any directory on a local file system or network share - but this default behavior might be changed in a future release.

  `AllowedInputDirectories` restricts the directories from which Media Server can read source media, training data, session configuration files, Lua scripts, XSL transforms and so on. Sending files to Media Server using an HTTP POST request (for example when you send the content of a file in a `multipart/form-data` request or as base-64 encoded data) is unaffected.

  Media Server is automatically permitted to read files from some locations that are configured in the `[Paths]` section of the configuration file. For example, configuration files can still be read from the `ConfigDirectory` and its subfolders, and Lua scripts can be read from the configured `LuaDirectory`. For more information, refer to the documentation for the new `AllowedInputDirectories` parameter.

- Color dictionaries and OCR user dictionaries can be uploaded as part of a `process` action, using the existing `AdditionalData` and `AdditionalDataLabels` parameters.

- Speed improvements in OCR alphabet and orientation detection.

- You can run Media Server without FFmpeg. FFmpeg is an open-source third-party component licensed under the GNU LGPL. Media Server uses FFmpeg when processing audio and video. The location of the FFmpeg libraries is specified by the `FFmpegDirectory` parameter in the `[Paths]` section of your Media Server configuration file. Media Server now starts successfully when this parameter is not set. Without FFmpeg, Media Server starts faster and requires less memory. However, a significant amount of Media Server functionality is unavailable. For more information, see the documentation for the `FFmpegDirectory` parameter.

### Resolved Issues

There were no resolved issues in this release.

### Notes

- Due to the security improvements described above, you might need to update your Media Server configuration file and session configuration files:

  - In scene filter tasks, relative paths in the `BackgroundImage` parameter must be relative to `[Paths]UserDataDirectory`. In earlier versions of Media Server, these paths were relative to `[Paths]ConfigDirectory`.
  - The `UserDataDirectory` parameter, in the `[Paths]` section of the Media Server configuration file, no longer has a default value. If your Media Server configuration does not set `UserDataDirectory`, you might need to set this parameter or update session configurations that include OCR tasks with custom dictionaries.

## 24.4.0

### New Features

- Media Server has a new transform engine (`Type=AudioChannelExtract`) that extracts a single channel from an audio track. For example, you can extract the left or right channel and analyze it separately.
- The person analysis engine has been improved. The accuracy of the `upperColor`, `upperStyle`, `lowerColor`, `lowerStyle`, and `gender` classifiers has been improved. The `lowerColor` classifier now returns the same range of colors as the `upperColor` classifier. The `lowerStyle` classifier includes a new class "Long Skirt/Robe".
- Speech-to-text custom word databases are supported by the new speech-to-text models (micro, small, medium, and large), but currently only with non-CJK languages. You can create custom word databases to improve accuracy when your audio includes uncommon words like product names.

### Resolved Issues

- (Security update) The third-party FFmpeg library was updated to version 7.0.
- OCR would sometimes output bounding boxes that had zero width or height.
- In text extracted from PDF files, extra spaces would sometimes appear in the middle of words.
- Media Server could terminate unexpectedly when running table analysis during OCR on some PDF files.
- The error "WARNING: SET TRANSACTION can only be used in transaction blocks" could appear in the PostgreSQL logs when using an external PostgreSQL training database. Media Server now correctly sets the transaction isolation level.

## 24.3.0

### New Features

- A new speaker ID algorithm provides improved accuracy and makes speaker ID easier to train. The new algorithm always operates in open-set mode: a speaker is classified as unknown when the confidence score fails to meet the value of the new parameter `MatchThreshold`. When training speaker ID, you no longer need to provide audio samples from "unknown" speakers.
- The new speech-to-text models have been improved. When processing non-English speech there is a new model (`medium`) that provides greater accuracy than the `small` model and better performance than the `large` model. The `large` English model has been renamed to `medium` for consistency (so that the `medium` and `large` names accurately indicate resource requirements).
- The new speech-to-text models produce better output when transcribing Chinese and Japanese. Media Server now produces a separate record for each word. Earlier versions could output multiple words per record when processing these languages.
- When you use OCR to read a news ticker, Media Server produces a result record for each headline. Earlier versions of Media Server would typically produce a single record for the entire video, containing all of the text.
- In the OCR analysis engine, the accuracy of alphabet detection has improved.
- The action `ValidateProcessConfig` has a new parameter, `DatabaseChecks`. This specifies whether to fail validation when a trained model (for example an image classifier or object class recognizer) is specified in the configuration but does not exist in the database. To preserve backwards compatibility, the default value of this parameter is `FALSE`.

### Resolved Issues

- (Security update) The third-party openjpeg library was updated to version 2.5.2.
- (Security update) The third-party thrift library was updated to version 0.20.0.
- (Security update) The third-party libde265 library was updated to version 1.0.15.
- (Security update) The third-party libheif library was updated to version 1.17.6.
- The new speech-to-text models would produce output in Traditional Chinese, rather than Simplified Chinese, when `LanguagePack=ZHCN`.
- Non-legacy speech-to-text would immediately fail with the error "bad language code" when the chosen language was `CYUK`, `SKSK`, or `SVSE`.
- Media Server could terminate unexpectedly when performing OCR on video, with `SceneAlgorithmBias=accuracy`.
- The `alphabet` field in `PageResult` records, from the OCR analysis engine, could include alphabets that were not present in the image.
- When a training action (for example `TrainFace` or `TrainObject`) did not specify an identifier, the automatically-generated identifier was not returned in the response (accessible through the `QueueInfo` action).
- A training action that moved a training image (for example `MoveFace` or `MoveObject`) would fail if the training image had a status of `failed`.

### Notes

- There have been significant changes in speaker ID following the introduction of the new speaker ID algorithm.

  - The action `CreateSpeakerDatabase` no longer has a `SampleFrequency` parameter, because setting this is no longer required.
  - The action `AddSpeakerAudio` no longer has a `Training` parameter. In previous versions of Media Server, some audio samples were designated (by setting `Training=False`) for use in estimating speaker thresholds, but this is no longer required.
  - The response to the action `ListSpeakers` has changed.

  - The following training actions have been removed:

    - AddUnknownSpeakerAudio
    - EstimateAllSpeakerThresholds
    - EstimateSpeakerThreshold
    - GetUnknownSpeakerAudio
    - ListUnknownSpeakerAudio
    - NullUnknownSpeakerAudioData
    - RemoveUnknownSpeakerAudio
    - SetSpeakerThreshold
  - The `ClosedSet` parameter has been removed from the speaker ID analysis engine. You can remove this parameter from your session configurations.

## 24.2.0

### New Features

- Media Server has a new analysis engine (`Type=ImageEmbedding`) to generate embeddings. An embedding is a numerical representation of an image, in the form of a vector that you can index into your IDOL Content component. IDOL Content can compare embeddings to other embeddings, to see whether two images are conceptually similar. If you have a pair of encoders, one trained to generate vectors from images and the corresponding one to generate vectors from text, you can use IDOL Content to search for images that are conceptually similar to keywords.
- The OCR parameter `Languages` accepts the value `ALL`, for cases when you do not know which language(s) to expect.

### Resolved Issues

- Media Server could terminate unexpectedly when speech-to-text was configured with `LanguagePack=Input` but was not configured to receive language ID results.
- Speech-to-text accuracy was reduced when processing non-English audio with a duration greater than 30 seconds. This issue was introduced in Media Server 24.1 and only affects the new speech-to-text models (`ModelVersion=micro/small/large`, but not `ModelVersion=legacy`). The warning "Detected unsupported language" would appear in the log file `engine.log`.

## 24.1.0

### New Features

- Face Demographics has significantly improved accuracy when recognizing age, gender, and ethnicity.
- Optical Character Recognition recognizes tables that are constructed from text elements in PDF files. In earlier versions of Media Server, OCR identified tabular data only in images.
- Optical Character Recognition uses a new algorithm for finding text in scene mode. The new algorithm uses a neural net and is more accurate but slower. The new algorithm is used by default but if you prefer to prioritize processing speed you can switch to the algorithm used in earlier versions, by setting `SceneAlgorithmBias=speed`.
- Optical Character Recognition is faster when processing video subtitles.
- Language identification results can be routed to a speech-to-text task, so that you can detect the language of speech and then transcribe it in a single process request. To support this feature, the language ID analysis engine has a new output track named `ResultWithSource`, which includes the detected language and the audio. You can use this track as the input for your speech-to-text task - set `LanguagePack=input` rather than choosing a specific language. This feature is not available with legacy speech-to-text (`ModelVersion=legacy`).
- The `DescribeMedia` action includes information about subtitle (closed-caption) streams. This information has also been added to the `Proxy` track of the video ingest engine.
- You can run face recognition and object recognition against multiple databases of faces/objects. (In earlier versions of Media Server you could choose either one database, or all databases.)
- The clip encoder can produce animated GIF thumbnails of events that occur in your video.
- The example Lua script that is provided for drawing analysis results on video (`configurations/lua/draw.lua`) supports text labels and tracking functionality.

### Resolved Issues

- (Security update) The third-party libwebp library was updated to version 1.3.2.
- (Security update) The third-party libpng library was updated to version 1.6.40.
- (Security update) The third-party libjpeg library was updated to version 9e.
- (Security update) The third-party libtiff library was updated to version 4.6.0.
- (Security update) The third-party protobuf library was updated to version 24.3. (This update does not apply when GPU acceleration is enabled, in which case Media Server still uses version 2.6.1).
- Following the improvements to the face detection algorithm in Media Server 23.4, face recognition (used with the same recognition threshold) could produce a different ratio of false positives to true negatives. Face recognition confidence scores have now been rescaled with the aim that a fixed recognition threshold should produce a consistent ratio of false positives to true negatives across Media Server versions.

### Notes

- The list of values that Face Demographics can return for a person's ethnicity has been updated:

  Media Server 23.4 | Media Server 24.1
  --- | ---
  `African/Caribbean` `Arab` `Caucasian` `East Asian` `Hispanic` `Indian Subcontinent` | `Arab` `Black` `East Asian` `Latino` `South Asian` `Southeast Asian` `White`

- The list of values that Face Demographics can return for a person's age has been updated:

  Label | Approximate Age
  --- | ---
  Media Server 23.4 | Media Server 24.1
  Baby | < 2 years | < 2 years
  Child | 2-15 years | 2-15 years
  Young Adult | 15-35 years | 15-30 years
  Adult | 35-55 years | 30-60 years
  Elderly | > 60 years | > 60 years

## 23.4.0

### New Features

- Face detection has significantly improved recall (fewer genuine faces are missed). For any chosen detection threshold, the new detector produces approximately the same proportion of false positives but significantly fewer false negatives. If you prefer to prioritize precision and have fewer false positives, you could increase the detection threshold because the new detector can achieve equivalent recall at a higher threshold. This improvement benefits downstream analysis such as face recognition, because faces that were not detected in previous versions can now be recognized.
- Face detection supports GPU acceleration and is much faster when you use a GPU for analysis. In earlier versions of Media Server, face detection did not use the GPU.
- Media Server can perform a new type of analysis called visual clustering. You can add a selection of video clips to the training database, and then run the action `ClusterVisualItems`. Media Server divides the videos into clusters of similar items and returns the results.
- Improved (reduced) memory usage when using a GPU with `CUDAVersion=11`.
- Improved pre-trained recognizers are available in the `MediaServerPretrainedModels` package. The new recognizers are labeled "large" or "small" - the large models provide the best accuracy while the small models prioritize faster analysis.
- Speech-to-text results now include ISO 8601 durations for alternate word offsets. In earlier versions of Media Server, the `startOffset` and `endOffset` values were provided only as a number of milliseconds.
- Optical Character Recognition (OCR) accuracy has improved when `OcrMode=Scene` and `HollowText=TRUE`.
- The `source` field in an `OCRResult` record can contain the value `image table`, which specifies that the text was extracted from a table in an image. In earlier versions of Media Server these records would have had the value `image`.

### Resolved Issues

- GPU acceleration did not work on Windows because some libraries were missing from the Media Server package.
- Media Server would give the error "Unsupported model version" when speech-to-text was configured to use the `micro` speech-to-text model.

### Notes

- Media Server 23.4 requests as many channels as it requires from your IDOL License Server, up to the maximum number available in your license, unless you configure the number of channels to request. (This is a change in the default behavior: earlier versions of Media Server did not request any channels by default and the number of channels you wanted to use had to be set in the configuration file). This means that you no longer need to configure the number of channels when running a single Media Server. However, if you are using multiple instances of Media Server, OpenText recommends that you specify the number of channels to use in each Media Server configuration file, to prevent just one of the servers from consuming all of the available channels.
- When training image classification or object class recognition, you can set the training option `validation_proportion` without setting `snapshot_frequency`. In this case Media Server uses the specified proportion of your training images to evaluate the performance of the final trained model. You can obtain the results of the evaluation through the action `GetObjectClassRecognizerSnapshotStatistics`.
- Some of the pre-trained recognizers that were available in the `MediaServerPretrainedModels` package have been removed, because other recognizers offer better accuracy or performance. `ObjectClassRecognizer_RoadScene`, `ObjectClassRecognizer_Person`, and `ObjectClassRecognizer_Gen3_PersonCar` have been removed because OpenText recommends using one of the surveillance recognizers instead. You can filter the output of a recognizer by setting the `ClassFilters` parameter in your analysis task. For example, to use a surveillance recognizer to recognize only people and cars, set `ClassFilters=person,car`.

## 23.3.0

### New Features

- Media Server supports a wider range of graphics cards for accelerating media analysis. Media Server now supports CUDA version 11 (compute capability version 3.5 to 8.6) in addition to the GPUs that were previously supported. For more information about using a GPU, refer to the Media Server Help.
- Media Server has a new analysis engine (`Type=PersonAnalysis`). Person analysis reports information about a person - for example their gender, clothing style and color, hair style and color, and hat style and color.
- The new speech-to-text algorithm (introduced in Media Server 23.2) now requires only the common speech-to-text resources. You no longer need to install legacy language packs such as `ENUK` or `ENUS`. The legacy language packs are still required for transcript alignment, speaker clustering, and for running speech-to-text if you set `ModelVersion=Legacy`.
- The new speech-to-text algorithm (introduced in Media Server 23.2) can output alternative words.
- The common resources for the new speech-to-text algorithm include a new model named `micro`. This model is faster - but less accurate - than the other models. It can be used on older or less powerful hardware that is unable to keep up with a live stream when using the `small` model. OpenText recommends that you try the `small` model first.
- The confidence score for a face recognition result is no longer affected by the value of the parameter `MaxRecognitionResults` (in earlier versions of Media Server there could be a small variation in confidence score for different values of this parameter).

### Resolved Issues

- Media Server could terminate unexpectedly when ingesting images with a very large number of pixels.
- An issue could occur when retraining `Generation1` object class recognizers. This issue has been resolved with a new database schema (version 13). OpenText recommends that you upgrade to the latest schema and consider retraining any `Generation1` recognizers.
- The XSL transformations `toIDX.xsl`, `toCSV.xsl`, and `toCFS.xsl` did not include the clothing region type.

### Notes

- The Media Server database schema has changed. If you are using an internal database, the schema upgrade is performed automatically when you start the new version of Media Server. If you are using an external MySQL database you must run an upgrade script, which is included in the Media Server 23.3 installation. For more information about upgrading the database schema, refer to the Media Server Help.

## 23.2.0

### New Features

- Media Server supports new speech-to-text models that offer significantly better accuracy, especially for English speech. The speech-to-text analysis engine has a new configuration parameter, `ModelVersion`. The default behavior (`ModelVersion=legacy`) uses the same models as Media Server 12.x. To use one of the new speech to text models you must set this parameter to either `small` (the fastest of the new models) or `large` (which offers the best accuracy). Custom language models and custom word dictionaries are neither necessary nor supported with the new models, because the vocabulary of the new models is not limited by their training. Due to their size, the new models are not included in the Media Server package and must be downloaded separately.
- Media Server can perform speaker clustering, which segments an audio recording into different speakers. There is a new analysis engine (`Type=ClusterSpeech`). Speaker clustering does not need training but does require that you install an appropriate speech-to-text language pack.
- Transcript alignment (`action=AlignAudioTranscript`) has a new parameter named `IngestDateTime`. You can use this to configure the start time for the timestamps. For example, set this parameter when you want the timestamps to match the time when the video was broadcast.
- Face recognition accuracy has been significantly improved.
- OCR accuracy has been improved when processing high resolution images in scene mode.
- The OCR `WordResult` track supports scrolling text (often seen below television news broadcasts).
- Strict action validation has been extended so that it validates any session configuration that you pass to a `process` action. When strict action validation is used, the `process` action will fail immediately if the configuration includes unknown parameters, or includes a configuration section that is referenced but contains no parameters.

### Resolved Issues

- Media Server could terminate unexpectedly when running Optical Character Recognition (OCR).
- Some temporary files produced by KeyView were written to the system temporary directory, rather than the location specified by the `TempDir` parameter in the `[Paths]` section of the configuration file. Some temporary files were not deleted when no longer required.

### Notes

- The older session configuration format, which was replaced in Media Server 12.0, is no longer supported. Media Server 23.2 only reads the list of processing tasks from the `[Session]` section of the configuration file. The older section names, such as `[Ingest]`, `[Analysis]`, `[Transform]`, `[Encoding]`, and `[Output]`, are now ignored.
- Media Server no longer supports the alias `Image_1` for the `Default_Image` track. In your session configuration files, replace `Image_1` with `Default_Image`. This change does not affect fully-qualified track names such as `TaskName.Image_1`, where `TaskName` is the name of an ingest task.
- The deprecated parameters `Language` and `CustomLM` have been removed from the speech-to-text analysis engine. Use the `LanguagePack` and `CustomLanguageModel` parameters instead.
- Strict action validation has been enabled by default. If you prefer to disable this, set the configuration parameter `StrictActionValidation=FALSE` in the `[Server]` section of the configuration file.
- The records in the OCR `WordData` and `WordResult` tracks now have unique UUIDs for each word. In earlier versions of Media Server all of the words on the same line had the same UUID. Now, there is a unique UUID for each word and the `parentID` field provides the UUID of the parent line.

## Deprecated Features

The following features are deprecated and might be removed in a future release.

Category | Deprecated Feature | Deprecated Since
--- | --- | ---
Speech-to-text | The value `Medium` for the configuration parameter `ModelVersion`, has been deprecated. OpenText recommends setting `ModelVersion=Large`. | 26.3.0
OCR | The `KeepOnly` configuration parameter. | 26.2.0
MPEG Encoder | The `MIMEType` configuration parameter. Media Server can determine the correct MIME type from the value of the `Format` or `OutputPath` parameter. | 26.2.0
Analysis engines | The clothing analysis engine (`Type=Clothing`) has been deprecated. OpenText recommends using the person analysis engine instead. | 24.4.0
Actions | The `activity` action. The graphical user interface (`action=GraphicalUserInterface`) provides similar functionality. | 24.3.0
Actions | The `GetLatestRecord` action. The new actions `KeepLatestRecords` and `GetLatestRecords` provide more control over what to store and retrieve. | 12.5.0

Copyright 2026 Open Text
Version 26.3.0 | Last updated July 2026

Send documentation feedback

Close

Send documentation feedback

To send feedback using your default email client, open an email window.

Otherwise, send your feedback and the information below to MFI-swpdl.idoldocsfeedback@opentext.com.

We appreciate your feedback!

Product: Knowledge Discovery 26.3.0

Topic Title: Media Server