genshiai-stt 2.0.0

GENSHI Works STT SDK — high-accuracy domain-specific speech-to-text

GENSHI Works STT SDK

High-accuracy domain-specific speech-to-text SDK. Supports batch transcription and realtime streaming with built-in VAD and on-device STT inference.

Installation

Python

pip install genshiai-stt

# With native runtime (recommended for production):
pip install genshiai-stt[native]

Node.js

npm install @genshiai/stt

The correct native addon for your platform is installed automatically via optional dependencies.

Browser

npm install @genshiai/stt-web

Quick Start

Python

import asyncio

from genshi_stt import GenshiSTTClient

async def main() -> None:
    async with GenshiSTTClient(api_key="gw-...") as client:
        with open("recording.wav", "rb") as f:
            result = await client.transcribe(f.read())
        print(result.text)

        async with client.stream(
            domain="medical",
            secure=True,
            effort="normal",
            dictionary_ids=["dict_hospital"],
            dictionaries=[
                {
                    "id": "dict_hospital",
                    "name": "院内用語",
                    "industry": "medical",
                    "terms": [{"term": "GENSHI AI", "reading": "げんしえーあい"}],
                }
            ],
        ) as session:
            partials = await session.push(audio_chunk)  # PCM16 bytes
            print(partials[0].text if partials else "")

            refined = await session.drain_events()
            for event in refined:
                if event.type == "refined":
                    print(event.index, event.text)

            final = await session.finalize()
            print(final.text)

asyncio.run(main())

Node.js / TypeScript

import { GenshiSTTClient } from '@genshiai/stt';

const client = new GenshiSTTClient({ apiKey: 'gw-...' });

// Batch transcription
const result = await client.transcribe(audioBuffer);
console.log(result.text);

// Realtime streaming
const session = client.stream({
  domain: 'medical',
  secure: true,
  effort: 'normal',
  dictionaryIds: ['dict_hospital'],
  dictionaries: [
    {
      id: 'dict_hospital',
      name: '院内用語',
      industry: 'medical',
      terms: [{ term: 'GENSHI AI', reading: 'げんしえーあい' }],
    },
  ],
});
const partials = await session.push(pcm16Chunk);
console.log(partials[0]?.text);

const refined = await session.drainEvents();
for (const event of refined) {
  if (event.type === 'refined') {
    console.log(event.index, event.text);
  }
}

const final = await session.finalize();
console.log(final.text);

Browser

import { GenshiSTTClient, createMicStream } from '@genshiai/stt-web';

const client = new GenshiSTTClient({ apiKey: 'gw-...' });
await client.init();

const session = client.stream({
  domain: 'medical',
  secure: true,
  effort: 'normal',
  dictionaryIds: ['dict_hospital'],
  dictionaries: [
    {
      id: 'dict_hospital',
      name: '院内用語',
      industry: 'medical',
      terms: [{ term: 'GENSHI AI', reading: 'げんしえーあい' }],
    },
  ],
});

const mic = await createMicStream();
mic.onAudio(async (chunk) => {
  const partials = await session.push(chunk);
  console.log(partials[0]?.text);

  const refined = await session.drainEvents();
  for (const event of refined) {
    if (event.type === 'refined') {
      console.log(event.index, event.text);
    }
  }
});

// When done:
const result = await session.finalize();
console.log(result.text);

Prefer await session.finalize() when you need the final corrected text. await session.close() now performs a best-effort finalize for cleanup. Use session.abort() only for intentional force-abort without billing finalize.

Choosing A Mode

Mode	During recording	Correction cadence	Recommended for
batch	Nothing is emitted until the request finishes	One final full-text pass	File upload, post-processing
realtime + effort="normal"	partial text appears immediately	Background correction is sparse	Dictation, meeting notes, standard live input
realtime + effort="high"	partial text appears immediately	Background correction is more frequent	Live captions, simultaneous charting, terminology-sensitive input

Realtime Mental Model

• push() returns immediate partial events from local STT
• drain_events() / drainEvents() returns queued refined / error events from background correction
• effort: "normal" batches corrections sparsely, effort: "high" refines more often
• finalize() still performs the final full-text correction pass

secure=True / secure: true requests the Secure tier. Secure requests require an industry domain such as medical, or inline custom dictionaries. Public SDK configuration is intentionally centered on domain, secure, dictionaryIds / dictionaries, and effort. Low-level VAD and local model tuning are not part of the public API.

Realtime Event Example

push() returns a partial event:

{
  "type": "partial",
  "text": "ほんじつのけつあつは130の80です。",
  "raw_text": "ほんじつのけつあつは130の80です。",
  "index": 0,
  "processing_time_ms": 0
}

drain_events() / drainEvents() returns a refined event for the same segment:

{
  "type": "refined",
  "text": "本日の血圧は130の80です。",
  "raw_text": "ほんじつのけつあつは130の80です。",
  "index": 0,
  "processing_time_ms": 88
}

Response

{
  "text": "今日は天気がいい",
  "raw_text": "きょうわ天気がいい",
  "processing_time_ms": 142,
  "segments": ["今日は天気がいい"]
}

Supported Platforms

Platform	Python	Node.js
macOS ARM64 (Apple Silicon)	genshiai-stt-native	@genshiai/stt-native-darwin-arm64
Linux x64	genshiai-stt-native	@genshiai/stt-native-linux-x64
Windows x64	genshiai-stt-native	@genshiai/stt-native-windows-x64
Browser	—	@genshiai/stt-web

Requirements

• Python >= 3.10 / Node.js >= 20
• Valid GENSHI Works API key
• ffmpeg (Node.js batch decode only)

Browser SDK note:

• await client.init() is required before transcribe() or realtime()
• the npm package includes JSON metadata, and secured ONNX assets are fetched via POST /v1/activate

Documentation

Full documentation: https://docs.genshi.ai/stt

License

Proprietary. Copyright (c) 2026 GENSHI Works Inc. All rights reserved. See LICENSE.