Automatic Speech Recognition

Turbo-optimized version of Whisper for fast speech-to-text conversions.

Large-scale speech recognition model geared for diverse applications.

C++ implementation of the Whisper model focused on efficiency.

Focuses on identifying speakers within conversational data.

Tailored for healthcare contexts, this model focuses on clearer communication.

Compact whispering model optimized for discreet conversations.

Large voice model aimed at robust and nuanced audio processing.

Model designed to identify and differentiate speakers in audio.

Multimodal model integrating multiple forms of input-output conversion.

Compact whisper model designed for voice retrieval applications.

A fast-paced variant of the Whisper model for improved performance.

A medium-sized model for efficient whisper recognition.

Identifies speech segments in audio waves for processing.

Base model for transcription and translation tasks.

A smaller model designed for Cantonese speech recognition.

An advanced model for rapid voice recognition.

A distilled version of Whisper for quicker outputs.

Transcribes Russian audio into text with high accuracy.

Dedicated to audio language learning and processing for diverse applications.

An ASR model for Indonesian language based on Wav2Vec architecture.

A language model trained for generating Hindi text.

Model for recognizing and processing Quranic text.

Arabic speech recognition model based on Wav2Vec architecture.

Wav2Vec model designed for Kazakh speech recognition.

Thai speech recognition model based on Wav2Vec architecture.

Ukrainian speech recognition model based on Wav2Vec architecture.

Model aimed at high-quality speech recognition.

Vietnamese speech recognition model utilizing Wav2Vec features.

Wav2Vec model for recognizing Basque language speech.

Model for low-resource speech recognition tasks.

Wav2Vec2 model designed for speech tasks in Czech.

Model specializing in Cantonese speech recognition tasks.

Wav2Vec2 model specialized in Arabic speech recognition.

ASR model focusing on speech recognition tasks in Japanese.

Dialect recognition model for improved speech processing.

Model for audio representation learning.

Fine-tuned version of HuBERT for improved speech recognition.

Extended HuBERT model for superior speech recognition performance.

Multilingual speech-to-text model for diverse languages.

Small model for automatic speech recognition tasks.

Audio model focused on speech representation learning.

Fine-tuned model for Spanish audio processing.

A robust model designed for speech recognition applications.

A large model focusing on advanced speech recognition.

Large model focused on general speech recognition tasks.

Fine-tuned robust model for high-performance speech recognition.

Optimized for speech recognition in conversational datasets.

Wav2Vec2 model specialized in Portuguese speech recognition.

Model focused on Spanish speech recognition tasks.

Fine-tuned model for speech recognition with an emphasis on pronunciation.

Specialized model for translating audio data directly into English text.

Fine-tuned Wav2Vec2 model focusing on speech recognition precision.

Wav2Vec2 model focused on Romanian speech recognition.

Large Wav2Vec2 model focused on Indonesian speech recognition.

Conformer model optimized for English speech recognition.

Wav2Vec2 model focused on Arabic speech representation.

Model designed for Chinese speech recognition tasks.

Wav2Vec2 model focused on Dutch speech recognition.

A large model for English speech recognition tasks.

Wav2Vec2 model designed for French speech recognition.

Persian-focused Wav2Vec2 model for speech analysis.

Model focused on Polish speech recognition tasks.

Russian Wav2Vec2 model equipped for speech recognition.

Wav2Vec2 model optimized for Spanish speech tasks.

Processes and transcribes Urdu speech into text.

Advanced speech recognition model for the Korean language.

Processes Brazilian Portuguese speech for transcription.

Transcribes Uyghur speech to text with high accuracy.

Classifies music genres from audio using wav2vec technology.

Transcribes Persian audio to text for diverse applications.

Recognizes emotions in Greek speech recordings.

Language model focused on Singaporean English.

Speech recognition model tailored for Turkish language.

Advanced speech processing tailored for Turkish.

Processes spoken Vietnamese for transcription tasks.

Turkish speech recognition model showcasing demo capabilities.

Detects moments of overlapping speech in audio recordings.

Segments audio recordings based on individual speakers.

Transforms audio signals into text for Mandarin Chinese.

Processes English audio for effective speech recognition.

Wav2Vec 2.0 model supporting multilingual speech recognition.

Wav2Vec2 model focused on Finnish language speech recognition.

BLSTM model designed for processing Farsi speech inputs.

Vietnamese Wav2Vec2 model for speech to text applications.

Wav2Vec2 model specialized for phoneme recognition tasks.

Voice model designed for Kabyle language recognition and generation.

Wav2Vec2 model focusing on recognizing spoken Darija Arabic.

Wav2Vec2 model optimized for understanding spoken Wolof.

Wav2Vec2 model designed for recognizing spoken Bambara.

Model specialized in speech recognition for the Serbian language.

Conformer model tailored for large-scale Mandarin speech recognition.

A HuBERT model for processing Egyptian Arabic speech.

Speech-to-text model focused on UK English dialect.

Wav2Vec model fine-tuned for Hindi audio transcription.

Medium-sized version of the Whisper model for audio tasks.

Large model designed for high-performance audio translation and transcription.

Tiny Whisper model for efficient transcription.

Base English language model in the Whisper lineup.

Small Whisper model focused on efficient audio processing.

Medium performance model in the Whisper series for English audio.

Large Wav2Vec model optimized for English phoneme recognition.

Large transducer model for Russian speech-to-text tasks.

Base Whisper model tailored for European languages.

Small Hindi Whisper model for audio transcription.

Model for converting pop melodies to piano arrangements.

A language model optimized for German speech recognition.

Generates narratives and imagery inspired by lunar themes.

Optimized for fast speech-to-text applications with high accuracy.

An ONNX-compatible model designed to improve machine learning efficiencies.