# rhasspy/piper

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10,584 stars · 910 forks · C++ · mit · archived

## Links

- GitHub: https://github.com/rhasspy/piper
- Homepage: https://rhasspy.github.io/piper-samples/
- awesome-repositories: https://awesome-repositories.com/repository/rhasspy-piper.md

## Topics

`speech-synthesis` `text-to-speech` `tts`

## Description

Piper is a local neural text-to-speech engine designed to convert written text into natural human speech entirely on your own hardware. By utilizing a neural synthesis framework, it operates without the need for internet connectivity, ensuring that all audio generation remains private and secure.

The system distinguishes itself through a modular architecture that allows for the dynamic loading of speaker embeddings and voice configurations. This enables users to switch between various vocal personas and styles without requiring a full reload of the core synthesis model. By processing input through a phoneme-based pipeline, the engine maintains consistent pronunciation and accurate prosody across different languages.

The framework supports real-time audio streaming, which processes and outputs speech segments as they are generated to minimize latency. It utilizes a high-fidelity synthesis approach that maps text sequences directly to audio waveforms, providing adjustable levels of complexity to suit different hardware performance requirements.

## Tags

### Artificial Intelligence & ML

- [Neural Text-to-Speech Engines](https://awesome-repositories.com/f/artificial-intelligence-ml/generative-ai-resources/speech-synthesis/neural-text-to-speech-engines.md) — Converts written text into natural human speech using a local neural synthesis framework based on VITS.
- [Local Speech Synthesis](https://awesome-repositories.com/f/artificial-intelligence-ml/text-to-speech/local-speech-synthesis.md) — Provides local text-to-speech synthesis on your own hardware without requiring internet connectivity.
- [Text-to-Speech](https://awesome-repositories.com/f/artificial-intelligence-ml/text-to-speech.md) — Converts written text into natural-sounding human speech using local neural synthesis models. ([source](https://rhasspy.github.io/piper-samples/))
- [On-Device Inference Engines](https://awesome-repositories.com/f/artificial-intelligence-ml/on-device-inference-engines.md) — Executes neural network models locally on host hardware to provide low-latency speech synthesis.
- [VITS Synthesis Models](https://awesome-repositories.com/f/artificial-intelligence-ml/generative-ai-resources/speech-synthesis/neural-text-to-speech-engines/vits-synthesis-models.md) — Generates high-fidelity audio waveforms by mapping text sequences directly to speech using VITS.
- [Speaker Embeddings](https://awesome-repositories.com/f/artificial-intelligence-ml/speaker-embeddings.md) — Supports dynamic loading of speaker embeddings to adjust vocal characteristics without reloading the core model.
- [Speech Synthesis Models](https://awesome-repositories.com/f/artificial-intelligence-ml/speech-synthesis-models.md) — A framework of high-quality voice models that transform text into speech with adjustable complexity.
- [Offline](https://awesome-repositories.com/f/artificial-intelligence-ml/voice-assistants/offline.md) — Supports the development of voice-enabled applications that function reliably without cloud connectivity.
- [Modular Voice Configurations](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning/speech-processing/voice-synthesis/modular-voice-configurations.md) — Enables dynamic switching between vocal personas by loading separate voice configuration files.
- [Conversational Audio Streams](https://awesome-repositories.com/f/artificial-intelligence-ml/text-to-speech/conversational-audio-streams.md) — Streams audio segments in real-time as they are generated to minimize latency.
- [Phoneme-Based Pipelines](https://awesome-repositories.com/f/artificial-intelligence-ml/sequence-alignment-models/phoneme-based-alignment/phoneme-based-pipelines.md) — Processes input through a phoneme-based pipeline to ensure consistent pronunciation and accurate prosody.
- [Phoneme-Based Speech Processors](https://awesome-repositories.com/f/artificial-intelligence-ml/text-to-speech/phoneme-based-speech-processors.md) — Utilizes a phoneme-based pipeline to ensure consistent pronunciation across different languages.
- [Voice Personalization](https://awesome-repositories.com/f/artificial-intelligence-ml/voice-assistants/voice-personalization.md) — Allows switching between various speaking styles and character voices within a single model. ([source](https://rhasspy.github.io/piper-samples/))

### Security & Cryptography

- [Privacy-Focused Processing](https://awesome-repositories.com/f/security-cryptography/privacy-focused-processing.md) — Ensures sensitive data remains private by processing all voice generation locally.

### Operating Systems & Systems Programming

- [Audio Buffers](https://awesome-repositories.com/f/operating-systems-systems-programming/kernel-core-internals/process-and-memory-management/memory-management/buffer-and-cache-management/binary-buffer-managers/trace-buffer-managers/audio-buffers.md) — Buffers audio segments in real-time to minimize latency during speech generation.
- [Real-Time Audio Streaming Buffers](https://awesome-repositories.com/f/operating-systems-systems-programming/kernel-core-internals/process-and-memory-management/memory-management/buffer-and-cache-management/binary-buffer-managers/trace-buffer-managers/audio-buffers/real-time-audio-streaming-buffers.md) — Buffers and outputs audio segments in real-time to minimize the delay between text input and playback.