fish-speech
SOTA Open Source TTS
Benchmark TTS quality and performance with Fish-Speech evaluation scripts. Measure WER, MOS, RTF, and throughput using Seed-TTS and EmergentTTS-Eval for accurate results.
How to Implement Custom Text Preprocessing Pipelines in Fish-SpeechLearn how to implement custom text preprocessing pipelines in Fish-Speech. Easily modify existing functions or create your own to enhance your audio processing.
How to Handle Out-of-Memory Errors During Training in Fish-SpeechLearn to handle out-of-memory errors in Fish-Speech training. Use mixed-precision, adjust batch size and max length, and enable gradient checkpointing to optimize memory usage.
How to Set Up Docker Deployment for Production with Fish SpeechLearn how to set up Docker deployment for production with Fish Speech. Deploy production-ready images for web interfaces and REST APIs with CUDA or CPU support and health checks.
How to Implement Real-Time Streaming TTS with Fish-SpeechImplement real-time streaming TTS effortlessly with Fish-Speech. Get synthesized WAV audio chunk-by-chunk via our production-ready HTTP API, eliminating wait times for instant audio.
How to Handle Multilingual TTS Without Phoneme Preprocessing in Fish-SpeechDiscover how Fish-Speech achieves multilingual TTS directly from Unicode text, bypassing phoneme preprocessing for seamless speech synthesis in numerous languages. Explore the unified approach.
How to Configure the Hydra Training Configuration in Fish-SpeechLearn to configure the Hydra training configuration in Fish-Speech using modular YAML files. Easily override parameters via command line or custom experiments without touching Python code.
How to Debug Common VQ Encoding Errors in Fish-SpeechEncountering VQ encoding errors in Fish-Speech? Learn how to debug them by checking model instances, audio shapes, sample rates, and tensor integrity for smoother audio processing.
How the TextToSemantic Lightning Module Handles Training in Fish SpeechLearn how the TextToSemantic Lightning module trains models. Discover its approach to optimizer configuration, loss computation, and LoRA checkpointing for efficient speech model development.
How to Implement Voice Cloning with Reference Audio in Fish-SpeechImplement voice cloning with reference audio using Fish-Speech. Learn how Fish-Speech encodes audio into tokens and injects them into a TTS model for realistic voice generation.
How to Configure the Fish-Speech API Server with Custom ParametersLearn to configure the Fish-Speech API server with custom parameters like listen, device, and API key. Easily adjust your API setup for optimal performance.
How to Quantize the Fish-Speech Model for Efficient InferenceLearn how to quantize the Fish-Speech model using INT8 and INT4 for efficient inference. Reduce model size by up to 8x while preserving generation quality.
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