Files
rustytorch/crates/models/rtx-csm/examples/stt_demo.rs
T
osobhandClaude Opus 4.7 adc9784646 rtx-csm: Stt::finish() — drain asr_delay buffer at end-of-stream
Phase 8.1.1 quality fix from the perf plan. Tokens emitted at LM step
`t` correspond to audio frame `t - ASR_DELAY_FRAMES` (6 frames /
0.48 s), so when a caller stops feeding audio without trailing
silence the last few words trail off — they're still inside the
delay pipeline.

finish() now steps ASR_DELAY_FRAMES additional silent frames after
handling any partial sub-frame buffer, giving the LM the chance to
emit those buffered tokens. Cost: 7 extra step_pcm calls per turn.

Verified end-to-end via stt_demo on a mid-utterance trim of the
LibriSpeech reference clip:
  pre-flush:  11 words ("...turnips and carrots and bruised")
  post-flush: 13 words ("...turnips and carrots and bruised potatoes and")

Also drops the now-redundant 2s silence suffix in stt_demo — the
flush replaces it. Affects converse_server's real-time end-of-turn
path where suffix padding wasn't possible.

Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]>
2026-04-29 04:02:19 -07:00

137 lines
4.5 KiB
Rust

//! Streaming STT demo: transcribe a WAV via Kyutai's 1B en/fr model.
//!
//! First run downloads ~3 GB from `kyutai/stt-1b-en_fr` to the HF cache.
//!
//! Usage:
//! ```
//! cargo run -p rtx-csm --release --features metal --example stt_demo -- \
//! --in /tmp/csm_24k.wav
//! ```
//!
//! Note: until sentencepiece detok is wired (Phase 6a polish), the output
//! is raw token IDs per word. The first version is intentionally minimal —
//! demonstrates that the streaming pipeline is connected end to end.
use anyhow::Result;
use clap::Parser;
use rtx_csm::{
audio_io,
stt::{AsrEvent, SAMPLE_RATE, Stt},
};
use std::path::PathBuf;
#[derive(Debug, Parser)]
#[command(name = "stt_demo")]
struct Cli {
/// Input WAV (any rate / channels — resampled to 24 kHz mono).
#[arg(long = "in")]
input: PathBuf,
/// Force CPU device.
#[arg(long)]
cpu: bool,
}
fn main() -> Result<()> {
tracing_subscriber::fmt().init();
let cli = Cli::parse();
let device = if cli.cpu {
candle_core::Device::Cpu
} else if candle_core::utils::metal_is_available() {
candle_core::Device::new_metal(0)?
} else {
candle_core::Device::Cpu
};
println!("device: {device:?}");
let t = std::time::Instant::now();
let mut stt = Stt::load_default(&device)?;
println!(
"loaded Kyutai STT 1B en/fr in {:.2}s",
t.elapsed().as_secs_f32()
);
// Load WAV at 24 kHz mono (Mimi's expected input rate).
let samples = audio_io::load_mono_at_rate(&cli.input, SAMPLE_RATE)?;
println!(
"loaded {}: {} samples ({:.2}s @ {} Hz)",
cli.input.display(),
samples.len(),
samples.len() as f32 / SAMPLE_RATE as f32,
SAMPLE_RATE
);
// The 1B en/fr STT model needs a few frames of silence after real audio
// to drain the asr_delay buffer (tokens at LM step `t` correspond to
// audio frame `t - 6`). `Stt::finish()` does that automatically — feed
// raw audio and then call finish().
const PREFIX_SILENCE_SECS: f32 = 0.0;
const SUFFIX_SILENCE_SECS: f32 = 0.0;
let mut audio_with_padding = vec![0.0f32; (PREFIX_SILENCE_SECS * SAMPLE_RATE as f32) as usize];
audio_with_padding.extend_from_slice(&samples);
audio_with_padding.extend(
std::iter::repeat(0.0f32).take((SUFFIX_SILENCE_SECS * SAMPLE_RATE as f32) as usize),
);
println!(
"padded with {:.1}s prefix + {:.1}s suffix silence -> {} samples",
PREFIX_SILENCE_SECS,
SUFFIX_SILENCE_SECS,
audio_with_padding.len()
);
// Stream in 1-second chunks so we can observe streaming behavior.
let chunk_size = SAMPLE_RATE as usize;
let mut all_events: Vec<AsrEvent> = Vec::new();
let t = std::time::Instant::now();
for (i, chunk) in audio_with_padding.chunks(chunk_size).enumerate() {
let evs = stt.step_pcm(chunk)?;
let n_step = evs
.iter()
.filter(|e| matches!(e, AsrEvent::Step { .. }))
.count();
let n_word = evs
.iter()
.filter(|e| matches!(e, AsrEvent::Word { .. }))
.count();
let n_end = evs
.iter()
.filter(|e| matches!(e, AsrEvent::EndWord { .. }))
.count();
println!("[chunk {i}] events: step={n_step} word={n_word} endword={n_end}");
all_events.extend(evs);
}
let evs_finish = stt.finish()?;
all_events.extend(evs_finish);
println!("inference: {:.2}s", t.elapsed().as_secs_f32());
// Pair Word with the next EndWord to get full timing, then detokenize.
let mut words = 0usize;
let mut full_text = String::new();
let mut pending: Option<(Vec<u32>, f64)> = None;
for ev in &all_events {
match ev {
AsrEvent::Word {
tokens, start_time, ..
} => {
pending = Some((tokens.clone(), *start_time));
}
AsrEvent::EndWord { stop_time, .. } => {
if let Some((tokens, start)) = pending.take() {
let text = stt.decode_word_text(&tokens).unwrap_or_default();
println!(" ({:.2}s - {:.2}s) {}", start, stop_time, text);
if !full_text.is_empty() && !text.is_empty() {
full_text.push(' ');
}
full_text.push_str(&text);
words += 1;
}
}
AsrEvent::Step { .. } => {}
}
}
println!("\n== transcript ({} words) ==", words);
println!("{}", full_text.trim());
Ok(())
}