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Ecoute is a live transcription tool that provides real-time transcripts for both the user's microphone input (You) and the user's speakers output (Speaker) in a textbox.
The main features of sevask/ecoute are: Real-Time Transcription, Local Speech-to-Text, Speech Recognition Engines, Combined Microphone and System Audio Captures, Transcription Provider Switching, Speech Recognition APIs, Speech-to-Text Integrations, Speech to Text Transcription.
Open-source alternatives to sevask/ecoute include: getstream/vision-agents. alphacep/vosk-api — Vosk is an offline speech-to-text engine and API that converts spoken audio into text locally on a device. It provides… k2-fsa/sherpa-onnx — Sherpa-ONNX is an ONNX-based speech processing toolkit that provides a local speech recognition engine, an on-device… cmusphinx/pocketsphinx — PocketSphinx is an offline speech recognition engine that converts raw audio from files or live microphone streams… koljab/realtimestt — RealtimeSTT is a local speech-to-text engine and real-time automatic speech recognition server. It utilizes… pipecat-ai/pipecat — Pipecat is a framework and software development kit for building real-time multimodal AI agents and speech-to-speech…
Vosk is an offline speech-to-text engine and API that converts spoken audio into text locally on a device. It provides a cross-platform speech toolkit with language bindings for integrating voice recognition into server environments, Android, iOS, and Raspberry Pi. The project includes a speaker identification tool to distinguish between different voices and an acoustic model trainer for building custom neural network models. These training tools enable speech feature extraction and model accuracy evaluation to improve recognition for specialized domains. The system supports real-time audio
Sherpa-ONNX is an ONNX-based speech processing toolkit that provides a local speech recognition engine, an on-device voice synthesis tool, and a speaker identification framework. It is designed as a cross-platform speech API that enables speech-to-text, text-to-speech, and speaker verification tasks to be executed locally on a device without requiring network access. The project is distinguished by its ability to perform zero-shot voice cloning and speaker diarization on-device. It supports a wide range of hardware accelerations, including GPU and various NPU architectures, and provides a Web
PocketSphinx is an offline speech recognition engine that converts raw audio from files or live microphone streams into written text without requiring a network connection. It functions as a speech-to-text library, a real-time transcription engine, and a voice command processor, capable of detecting and transcribing spoken commands from continuous audio streams with configurable acoustic and language models. The engine uses weighted finite-state transducers to represent acoustic, phonetic, and language models as a single search graph for efficient decoding. It employs fixed-point acoustic mod
