Audio format

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Python — sphn

import sphn, base64
import numpy as np

writer = sphn.OpusStreamWriter(24000)   # one per session
reader = sphn.OpusStreamReader(24000)   # one per session

# Encode: float32 PCM in [-1, 1] at 24 kHz → base64 Opus.
# append_pcm returns the encoded bytes (may be empty while it buffers).
def encode(pcm_f32: np.ndarray) -> str | None:
    data = writer.append_pcm(pcm_f32)
    return base64.b64encode(data).decode() if data else None

# Decode: base64 Opus → float32 PCM at 24 kHz.
# append_bytes returns the decoded samples (may be empty mid-packet).
def decode(b64: str) -> np.ndarray:
    return reader.append_bytes(base64.b64decode(b64))

from scipy.signal import resample_poly
pcm_24k = resample_poly(pcm_16k, up=3, down=2)

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Node.js

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Browser

• WebCodecs (Chrome/Edge): AudioEncoder/AudioDecoder with codec: "opus", sampleRate: 24000, numberOfChannels: 1. Capture the mic with getUserMedia + AudioWorklet, resample to 24 kHz in the worklet if the context runs at 48 kHz.
• opus-recorder (wider support): WASM Opus encoder with a configurable encoderSampleRate: 24000.

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Chunking and pacing

• Send audio in 20–80 ms chunks at real-time pace. Don’t dump a whole file at once — the turn engine reads timing, not just content, to decide when you’ve finished speaking.
• Keep sending silence between user utterances. A silent stream is how the engine knows the user is done; a stopped stream just looks like a stall.
• Output audio is mastered slightly quieter than typical TTS APIs — apply client-side gain if you need to match other sources.