…technologies setup. If we assume that the whole machine is dedicated as a “speech computing unit” then, in general, we can calculate it as follows: file: phxspe.properties server.n_workers = <#_of_core> file: technologies.xml (no. of threads per technology, can be also set up by the phxadmin tool) SQE: <#_of_cores>/4 VAD: <#_of_cores>/2 other technologies: <#_of_cores> RAM: 8 cores = 32 GB 16…
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…physical server, configure your technologies.xml to the following number of instances: SQE: <#_cpu_cores>/4 VAD: <#_cpu_cores>/2 any other technology: <#_cpu_cores> (Note: your license should also be configured properly. Ask our Sales department for cooperation in case of hot-load evaluation tests. The production license will be configured with our assistance, of course) Optimal RAM recommendation: 4 cores: 16 GB RAM 8 cores:…
…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…
…sentence. So, following the How to configure STT realtime stream word detection parameters article, we create a stt_cs_cz_5_online.bs.usr text file along the original stt_cs_cz_5_online.bs configuration file in <SPE directory>/bsapi/stt/settings directory and put the following lines in it (changing the forward extension parameter from default 750 to 1500): [vad.online_segmenter:SOnlineVoiceActivitySegmenterI] forward_extensions_length_ms=1500 Then after restarting SPE – and optionally checking in SPE log…
…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…
…recording, Speech to Text (STT) – several languages supported – converts speech into plain text (words or sentences) automatically, Keyword Spotting (KWS) – several languages supported – detects specific keywords/phrases automatically without conversion to text, Gender identification (GID) – identifies whether a speaker is male or female, Age Estimation (AGE) – estimates the speaker´s age group, Voice Activity Detection (VAD)…
MODULE 1: Getting started with Speech Engine (19 min) Installation Technologies configuration Server and database configuration Users configuration Files processing Synchronous and asynchronous requests, results polling Stream processing https://youtu.be/4qrB-GfFdWY…
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…
MODULE 3: Voice Biometrics technologies (23 min) Common generic rules for CLI, REST and GUI Speaker Identification (SID) in CLI, REST and GUI Language Identification (LID) in CLI, REST and GUI Gender Identification (GID) in CLI, REST and GUI Summary https://www.youtube.com/watch?v=AyEoPfYVel8…