# Real-time audio processing

This is a speaker segmentation model based on powerset encoding, capable of processing 10-second audio clips and identifying multiple speakers and their overlapping situations.

A speaker diarization model modified based on pyannote/speaker-diarization-3.0, using speechbrain/spkrec-ecapa-voxceleb for speaker embedding, with better performance in certain tests

Russian automatic speech recognition (ASR) model optimized based on OpenAI Whisper Large V3 Turbo, fine-tuned using the Mozilla Common Voice 17 Russian dataset

A pre-trained model based on the ECAPA-TDNN architecture for classifying gender from human speech

This is an audio processing model for speaker diarization, capable of detecting speech activity, overlapping speech, and multiple speakers.

Whisper large-v3 is a large-scale multilingual automatic speech recognition (ASR) model developed by OpenAI, supporting speech-to-text tasks in multiple languages.

An audio processing model for speaker segmentation that can automatically detect and segment different speakers in audio.

This is a powerset-encoded speaker diarization model capable of processing 10-second audio clips to identify multiple speakers and their overlapping speech.

This is the CTranslate2 converted version of OpenAI Whisper large-v2 model for efficient speech recognition

Speaker diarization model based on pyannote.audio 2.0 for automatic detection of speaker changes and speech activity in audio

A large-scale cross-lingual speech recognition model based on the Wav2Vec2 architecture, specifically optimized for Spanish, released by Facebook

An audio separation model trained based on the Asteroid framework, specifically designed for multi-channel audio signal separation tasks with noise

ConvTasNet model trained on the Asteroid framework for single-channel speech enhancement tasks

This model is a transfer learning-based Arabic speech recognition system specifically designed to identify Quran recitations and locate corresponding chapters.