modelscope/FunASR

Features

• Automatic Speech Recognition - Provides a comprehensive toolkit for automatic speech recognition, including local server hosting and multilingual support.
• Multilingual Transcription - Provides high-performance transcription services supporting over fifty languages with automatic language detection.
• Real-Time Transcription - Processes live audio streams to provide immediate, low-latency text transcriptions.
• Multilingual Speech-to-Text - Implements an engine capable of detecting languages and transcribing speech across fifty different languages.
• Multilingual Models - Employs a shared representation space to recognize and transcribe speech across more than fifty languages.
• Speaker Diarization - Identifies and labels different speakers within an audio stream to track participants over time.
• Speech Transcription - Utilizes advanced model architectures to transcribe spoken audio into text across multiple languages.
• Streaming Transcription Inference - Enables low-latency text output during live speech by processing audio in small incremental segments.
• Voice Activity Detection - Provides precise identification of the start and end timestamps of speech segments in audio streams.
• OpenAI-Compatible APIs - Exposes transcription endpoints using a standard OpenAI-compatible API format for easy integration with external tools.
• Transcription APIs - Provides a local server endpoint for programmatic access to automated speech transcription services.
• Audio Segmenting - Splits audio files into distinct sections by detecting voice activity and adjusting for silence thresholds.
• Controllable Speech Generation - Produces synthetic voice audio with adjustable controls for timbre and emotional expression.
• Inference Acceleration - Increases transcription throughput and reduces latency using parallel batch decoding techniques.
• Spoken Language Detection - Identifies the specific language being spoken from a wide range of supported multilingual options.
• Edge Model - Executes speech models on CPU or edge devices using self-contained binaries for high-performance inference.
• Speech Model Fine-Tuning - Supports distributed fine-tuning of speech models using custom datasets to increase recognition accuracy.
• Model Export and Portability - Supports exporting optimized speech models to ONNX format for high-performance inference on edge hardware.
• ONNX Model Exporters - Converts trained speech model weights into the portable ONNX format for execution across diverse hardware.
• ONNX Model Exports - Provides speech models exported to the Open Neural Network Exchange format for cross-hardware compatibility.
• Model Export Formats - Converts trained models into universal industry formats for deployment via containerized runtimes.
• Voice-to-Text Input Automation - Captures live microphone audio and inserts recognized words directly into the active cursor position of an application.
• Timestamped Subtitle Generators - Generates timed subtitle files in SRT or VTT formats by aligning transcribed text with audio timestamps.
• Inference Batching - Increases hardware throughput and inference speed by processing multiple audio streams simultaneously in batches.
• Audio Event Detection - Identifies non-speech sounds and speaker emotions to provide comprehensive contextual audio information.
• AI and Agents - Industrial-grade speech recognition toolkit with 170x realtime speed.
• Language Model Development - Production-grade toolkit for automatic speech recognition.
• Media and Content Creation - Performs industrial-grade speech recognition and transcription.

Star history