Search Results for: adaptation

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LID adaptation

Relevance: 100%      Posted on: 2021-03-02

This article describes various ways of Language Identification adaptation. Basic terminology Languageprint (*.lp file) – numeric representation of the audio, extracted from audio file for language identification purpose of (similar to “voiceprint”, but representing the spoken language, not the speaking person) Languageprint archive (*.lpa file) – multiple languageprints combined into single archive Creation of languageprint archives is not supported by SPE, these are supported as input only.   Language model – digital characteristics of a specific language Language model can be trained from languageprints (*.lp), language prints archives (*.lpa), or from combination of both. LID language model should not be…

Q: Please give me a recommendation for LID adaptation set.

Relevance: 69%      Posted on: 2017-06-27

A: The following is recommended: For adding new language to language pack 20+ hours of audio for each new language model (or 25+ hours of audio containing 80% of speech) Only 1 language per record For adapting the existing language model (discriminative training) 10+ hours of audio for each language May be done on customer site. May be done in Phonexia using anonymized data (= language-prints extracted from a .wav audio)

Language Identification (LID)

Relevance: 18%      Posted on: 2021-02-25

Phonexia Language Identification (LID) will help you distinguish the spoken language or dialect. It will enable your system to automatically route valuable calls to your experts in the given language or to send them to other software for analysis. Application areas Preselecting multilingual sources and routing audio streams/files to language dependent technologies (transcribing, indexing, etc.) Analyzing network traffic media (language statistics) Routing particular calls (languages) to human operators (language experts) Recognized languages Languages pre-trained in default language pack are listed in the table below, each LID generation is separate column (in the 4th generation we switched to using language tags…

Difference between on-the-fly and off-line type of transcription (STT)

Relevance: 4%      Posted on: 2017-12-11

Similarly as human, the ASR (STT) engine is doing the adaptation to an acoustic channel, environment and speaker. Also the ASR (STT) engine is learning more information about the content during time, that is used to improve recognition. The dictate engine, also known as on-the-fly transciption, does not look to the future and has information about just a few seconds of speech at the beginning of recordings. As the output is requested immediately during processing of the audio, recording engine can't predict what will come in next seconds of the speech. When access to the whole recording is granted during off-line transcription…


Relevance: 4%      Posted on: 2017-06-15

Document which briefly describes processes and relations in Phonexia Technologies with consideration on correct word usage.   SID - Speaker Identification Technology (about SID technology) which recognize the speaker in the audio based on the input data (usually database of voiceprints). XL3, L3,L2,S2 - Technology models of SID. Speaker enrollment - Process, where the speaker model is created (usually new record in the voiceprint database). Speaker model: 1/ should reach recommended minimums (net speech, audio quality), 2/ should be made with more net speech and thus be more robust. The test recordings (payload) are then compared to the model (see…