Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Support for HLS transcription (resolves #62) #73

Merged
merged 3 commits into from
Dec 12, 2023
Merged
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
6 changes: 6 additions & 0 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -41,6 +41,12 @@ Unlike traditional speech recognition systems that rely on continuous audio stre
```
This command captures audio from the microphone and sends it to the server for transcription. It uses the same options as the previous command, enabling the multilingual feature and specifying the target language and task.

- To trasncribe from a HLS stream:
```python
client = TranscriptionClient(host, port, is_multilingual=True, lang="en", translate=False)
client(hls_url="http://as-hls-ww-live.akamaized.net/pool_904/live/ww/bbc_1xtra/bbc_1xtra.isml/bbc_1xtra-audio%3d96000.norewind.m3u8")
```
This command streams audio into the server from a HLS stream. It uses the same options as the previous command, enabling the multilingual feature and specifying the target language and task.

## Transcribe audio from browser
- Run the server
Expand Down
44 changes: 41 additions & 3 deletions whisper_live/client.py
Original file line number Diff line number Diff line change
Expand Up @@ -344,6 +344,42 @@ def write_audio_frames_to_file(self, frames, file_name):
wavfile.setframerate(self.rate)
wavfile.writeframes(frames)

def process_hls_stream(self, hls_url):
"""
Connect to an HLS source, process the audio stream, and send it for transcription.

Args:
hls_url (str): The URL of the HLS stream source.
"""
print("[INFO]: Connecting to HLS stream...")
process = None # Initialize process to None

try:
# Connecting to the HLS stream using ffmpeg-python
process = (
ffmpeg
.input(hls_url, threads=0)
.output('-', format='s16le', acodec='pcm_s16le', ac=1, ar=self.rate)
.run_async(pipe_stdout=True, pipe_stderr=True)
)

# Process the stream
while True:
in_bytes = process.stdout.read(self.chunk * 2) # 2 bytes per sample
if not in_bytes:
break
audio_array = self.bytes_to_float_array(in_bytes)
self.send_packet_to_server(audio_array.tobytes())

except Exception as e:
print(f"[ERROR]: Failed to connect to HLS stream: {e}")
finally:
if process:
process.kill()

print("[INFO]: HLS stream processing finished.")


def record(self, out_file="output_recording.wav"):
"""
Record audio data from the input stream and save it to a WAV file.
Expand Down Expand Up @@ -464,7 +500,7 @@ class TranscriptionClient:
def __init__(self, host, port, is_multilingual=False, lang=None, translate=False):
self.client = Client(host, port, is_multilingual, lang, translate)

def __call__(self, audio=None):
def __call__(self, audio=None, hls_url=None):
"""
Start the transcription process.

Expand All @@ -483,8 +519,10 @@ def __call__(self, audio=None):
return
pass
print("[INFO]: Server Ready!")
if audio is not None:
if hls_url is not None:
self.client.process_hls_stream(hls_url)
elif audio is not None:
resampled_file = resample(audio)
self.client.play_file(resampled_file)
else:
self.client.record()
self.client.record()