Phonexia Phoneme Recogniser (PHNREC) converts speech signals into pronunciation characters (so called phonemes). After the conversion, the pronunciation (text) can be easily indexed and searched by third party text data mining tools. The technology is optimized for noisy recordings and colloquial speech, can process audio files as well as audio streams and can provide results in several output formats. Phoneme…
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…(the first model of 5th generation) [BSAPI] Added more accurate G2P (5th generation only) [BSAPI#72] Fixed phoneme recognizer doesn’t make phonemes for phnrec_ru_ru.bs [BSAPI#99] Fixed phoneme recognizer with configuration phnrec_cs_cz.bs doesn’t transcript short recordings [BSAPI#82] Fixed missing configuration of phnrec for HR_HR4 [BSAPI#78] Fixed STT segmentation – a segment doesnt break on a long silence, creates false crosstalks [BSAPI#148] Phoneme…
…models have been released. So in accordance with our Phonexia Product Support Lifecycle Policy, we announce the end of life for the following models: technology model to be deprecated note: latest model STT + KWS + PHNREC EN4 English (United States) EN_US_6 English (United States) STT + KWS + PHNREC HR_HR4 Croatian (Croatia) HR_HR_6 Croatian (Croatia) Known Issues Some of…
…be especially the case of product- or brand names, domain-specific words, misspelled words, incorrectly pronounced foreign words, etc. Therefore it’s highly recommended to explicitly specify pronunciation (or multiple pronunciation variants) for keywords. The easiest way to specify a pronunciation is to start off with automatically generated pronunciation and modify it as needed. Alternatively a Phoneme Recognizer (PHNREC) can be used…
…name User configuration file name stt_cs_cz_5_online.bs stt_cs_cz_5_online.bs.usr kws_nl_nl_5.bs kws_nl_nl_5.bs.usr phnrec_pashto.bs phnrec_pashto.bs.usr vpextract4_xl4.bs vpextract4_xl4.bs.usr During technology initialization (e.g. during Speech Engine startup), the initialization routine checks for existence of such user config file. If found, it’s automatically loaded after loading the main configuration file and the settings from user config is automatically applied over the setings from main configuration file. Usage…
…results JSON data rest_result_gid GID processing results – file, used technology model, results JSON data rest_result_kws KWS processing results – file, used technology model, used keyword list, results JSON data rest_result_lid LID processing results – file, used technology model, used language pack, results JSON data rest_result_phnrec PHNREC processing results – file, used technology model, results JSON data rest_result_sid SID processing…
…120.wav ├── 150.wav ├── 180.wav ├── 210.wav ├── 240.wav ├── 270.wav └── 300.wav For majority of technologies, the content of default directory is used for the benchmarking. Benchmarking of the language-specific technologies – STT (Speech To Text) and PHNREC (Phoneme Recognizer) – first tries to find a directory with a name matching the start of the benchmarked model name and…
…only English models for Speech To Text and Keyword Spotting. Additional supported languages are available upon request. ⓘ Click to show/hide the package content Speech Engine – technologies included: Speech To Text (STT) – model EN_US_6 (US English) Keyword Spotting (KWS) – model EN_US_6 (US English) Phoneme Recognizer (PHNREC) – model EN_US_6 (US English) Speaker Identification 4 (SID4) – model…
…and their usages Filtering and supporting technologies 04:32 Speech Quality Estimation (SQE) 05:27 Voice Activity Detection (VAD) 06:37 Diarization (DIAR) 07:41 Age Estimation (AGE) 08:14 Waveform Denoiser Voice Biometrics technologies 08:56 Speaker Identification (SID) 10:18 Language Identification (LID) 11:10 Gender Identification (GID) Speech Analytics technologies 11:43 Speech Transcription (STT) 12:30 Keyword Spotting (KWS) 13:32 Phoneme Recognition (PHNREC) 13:54 Time Analysis…
…models VIN application (graphical user interface, GUI) with the following technologies in-build Speaker Identification (SID4_XL5) Speaker Diarization (DIAR) Voice Activity Detection (VAD) Speech Quality Estimator (SQE) Phoneme Recogniser (PHNREC) example population sets and audio (in ./examples/) and example report templates (in ./templates/) Hardware requirements minimum – CPU: Intel® Core™ i5, RAM: 4 GB, Required HDD space: 0.5 GB for software…
…– detects the audio part that contains voice, Speech Quality Estimation (SQE) – measures the quality of speech, Phoneme Recognizer (PHNREC) – several languages supported – converts speech into phonemes (written characters representing pronunciation), Waveform Denoiser (DENOISER) – automatically improves the audibility of speech for human listeners. Supported Languages The LID, STT and KWS technologies support various languages as listed…
…Diarization GID Gender Identification KWS Keyword Spotting KWS_STREAM Keyword Spotting Stream LIDC Language Identification Languageprint Comparator LIDE Language Identification Languageprint Extractor PHNREC Phoneme Recognition SID4C Speaker Identification 4 Voiceprint Comparator SID4C_STREAM Speaker Identification 4 Voiceprint Stream Comparator SID4CALIB Speaker Identification 4 VoicePrint Calibration SID4E Speaker Identification 4 Voiceprint Extractor SID4E_STREAM Speaker Identification 4 Voiceprint Stream Extractor SQE Speech Quality Estimation…
MODULE 4: Speech Analytics technologies (23 min) Common generic rules for CLI, REST and GUI Speech To Text (STT) in CLI, REST and GUI Keyword Spotting (KWS) in CLI, REST and GUI Phoneme Recognizer (PHNREC) in CLI, REST and GUI Time Analysis Extraction (TAE) in CLI, REST and GUI Summary https://www.youtube.com/watch?v=-FAoRywqv7U…