Spaces:
Running on Zero
Running on Zero
File size: 4,203 Bytes
338c6c4 0189aeb 338c6c4 0189aeb 338c6c4 0189aeb 338c6c4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 | """Gradio Space: forced alignment with Qwen3-ForcedAligner-0.6B.
Serves both:
1. A usable web UI for interactive alignment.
2. A programmatic API endpoint (`/align`), auto-exposed by Gradio, that
other services can call via `gradio_client.Client` — see
`examples/client_example.py`.
"""
from __future__ import annotations
# `spaces` must be imported before `torch` (imported transitively via
# `aligner`) so it can patch CUDA initialization for ZeroGPU Spaces. On
# non-ZeroGPU hardware (or local dev), `spaces.GPU` is a harmless no-op.
import spaces
import gradio as gr
from aligner import MAX_AUDIO_SECONDS, SUPPORTED_LANGUAGES, align
DATAFRAME_HEADERS = ["#", "Text", "Start (s)", "End (s)"]
EXAMPLE_AUDIO_URL = (
"https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen3-ASR-Repo/asr_zh.wav"
)
EXAMPLE_TEXT = "甚至出现交易几乎停滞的情况。"
@spaces.GPU(duration=120)
def run_alignment(audio, text: str, language: str):
"""Event handler for the UI button, and the function exposed as the API.
Returns (dataframe_rows, raw_json) so the UI shows both a readable
table and the full structured payload; API callers get the same tuple.
`@spaces.GPU` is required on ZeroGPU Spaces: it's how the ZeroGPU
scheduler detects which functions need a GPU attached and allocates one
for the duration of the call. Model loading happens lazily inside
`aligner.get_model()`, on first call to `align()` below, so it also
runs inside this GPU-attached window (required — CUDA calls made
outside a `@spaces.GPU` call fail on ZeroGPU hardware).
"""
try:
spans = align(audio=audio, text=text, language=language)
except Exception as exc: # surface a clean error instead of a traceback
raise gr.Error(str(exc)) from exc
rows = [[s.index, s.text, round(s.start_time, 3), round(s.end_time, 3)] for s in spans]
raw = [
{"index": s.index, "text": s.text, "start_time": s.start_time, "end_time": s.end_time}
for s in spans
]
return rows, raw
with gr.Blocks(title="Qwen3 Forced Aligner") as demo:
gr.Markdown(
"""
# Qwen3 Forced Aligner
Align a text transcript to its audio and get per-unit start/end timestamps,
powered by [Qwen/Qwen3-ForcedAligner-0.6B](https://huggingface.co/Qwen/Qwen3-ForcedAligner-0.6B).
Upload or record audio, paste the matching transcript, pick the language, and align.
This UI also doubles as an API — see the "Use via API" link at the bottom of the page.
"""
)
with gr.Row():
with gr.Column():
audio_input = gr.Audio(
sources=["upload", "microphone"],
type="filepath",
label="Audio",
)
text_input = gr.Textbox(
label="Text to align",
placeholder="Enter the transcript that matches the audio...",
lines=4,
)
language_input = gr.Dropdown(
choices=SUPPORTED_LANGUAGES,
value="English",
label="Language",
)
gr.Markdown(
f"_Max audio length: ~{MAX_AUDIO_SECONDS // 60} minutes per request._"
)
align_button = gr.Button("Align", variant="primary")
with gr.Column():
output_table = gr.Dataframe(
headers=DATAFRAME_HEADERS,
datatype=["number", "str", "number", "number"],
label="Aligned spans",
wrap=True,
)
with gr.Accordion("Raw JSON output", open=False):
output_json = gr.JSON(label="Raw result")
gr.Examples(
examples=[[EXAMPLE_AUDIO_URL, EXAMPLE_TEXT, "Chinese"]],
inputs=[audio_input, text_input, language_input],
)
align_button.click(
fn=run_alignment,
inputs=[audio_input, text_input, language_input],
outputs=[output_table, output_json],
api_name="align",
concurrency_limit=1, # one model instance on one GPU
)
demo.queue()
if __name__ == "__main__":
demo.launch(server_name="0.0.0.0", server_port=7860)
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