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Remove blank segment feature

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Signed-off-by: makaveli10 <vineet.suryan@collabora.com>
This commit is contained in:
makaveli10
2025-04-17 08:29:14 +00:00
parent 617f587699
commit 9b364f267a
4 changed files with 3 additions and 73 deletions
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whisper_live/backend/base.py
+2 -37
View File
@@ -20,19 +20,13 @@ class ServeClientBase(object):
self.text = []
self.current_out = ''
self.prev_out = ''
self.t_start = None
self.exit = False
self.same_output_count = 0
self.show_prev_out_thresh = 5 # if pause(no output from whisper) show previous output for 5 seconds
self.add_pause_thresh = 3 # add a blank to segment list as a pause(no speech) for 3 seconds
self.transcript = []
self.send_last_n_segments = 10
self.no_speech_thresh = 0.45
self.clip_audio = False
# text formatting
self.pick_previous_segments = 2
# threading
self.lock = threading.Lock()
@@ -45,9 +39,7 @@ class ServeClientBase(object):
If the client's language is not detected, it waits for 30 seconds of audio input to make a language prediction.
It utilizes the Whisper ASR model to transcribe the audio, continuously processing and streaming results. Segments
are sent to the client in real-time, and a history of segments is maintained to provide context.Pauses in speech
(no output from Whisper) are handled by showing the previous output for a set duration. A blank segment is added if
there is no speech for a specified duration to indicate a pause.
are sent to the client in real-time, and a history of segments is maintained to provide context.
Raises:
Exception: If there is an issue with audio processing or WebSocket communication.
@@ -85,7 +77,7 @@ class ServeClientBase(object):
def transcribe_audio(self):
raise NotImplementedError
def handle_transcription_output(self):
def handle_transcription_output(self, result, duration):
raise NotImplementedError
def format_segment(self, start, end, text, completed=False):
@@ -228,33 +220,6 @@ class ServeClientBase(object):
except Exception as e:
logging.error(f"[ERROR]: Sending data to client: {e}")
def get_previous_output(self):
"""
Retrieves previously generated transcription outputs if no new transcription is available
from the current audio chunks.
Checks the time since the last transcription output and, if it is within a specified
threshold, returns the most recent segments of transcribed text. It also manages
adding a pause (blank segment) to indicate a significant gap in speech based on a defined
threshold.
Returns:
segments (list): A list of transcription segments. This may include the most recent
transcribed text segments or a blank segment to indicate a pause
in speech.
"""
segments = []
if self.t_start is None:
self.t_start = time.time()
if time.time() - self.t_start < self.show_prev_out_thresh:
segments = self.prepare_segments()
# add a blank if there is no speech for 3 seconds
if len(self.text) and self.text[-1] != '':
if time.time() - self.t_start > self.add_pause_thresh:
self.text.append('')
return segments
def disconnect(self):
"""
Notify the client of disconnection and send a disconnect message.
whisper_live/backend/faster_whisper_backend.py
-30
View File
@@ -175,33 +175,6 @@ class ServeClientFasterWhisper(ServeClientBase):
self.set_language(info)
return result
def get_previous_output(self):
"""
Retrieves previously generated transcription outputs if no new transcription is available
from the current audio chunks.
Checks the time since the last transcription output and, if it is within a specified
threshold, returns the most recent segments of transcribed text. It also manages
adding a pause (blank segment) to indicate a significant gap in speech based on a defined
threshold.
Returns:
segments (list): A list of transcription segments. This may include the most recent
transcribed text segments or a blank segment to indicate a pause
in speech.
"""
segments = []
if self.t_start is None:
self.t_start = time.time()
if time.time() - self.t_start < self.show_prev_out_thresh:
segments = self.prepare_segments()
# add a blank if there is no speech for 3 seconds
if len(self.text) and self.text[-1] != '':
if time.time() - self.t_start > self.add_pause_thresh:
self.text.append('')
return segments
def handle_transcription_output(self, result, duration):
"""
Handle the transcription output, updating the transcript and sending data to the client.
@@ -215,9 +188,6 @@ class ServeClientFasterWhisper(ServeClientBase):
self.t_start = None
last_segment = self.update_segments(result, duration)
segments = self.prepare_segments(last_segment)
else:
# show previous output if there is pause i.e. no output from whisper
segments = self.get_previous_output()
if len(segments):
self.send_transcription_to_client(segments)
whisper_live/backend/openvino_backend.py
-3
View File
@@ -118,9 +118,6 @@ class ServeClientOpenVINO(ServeClientBase):
self.t_start = None
last_segment = self.update_segments(result, duration)
segments = self.prepare_segments(last_segment)
else:
# show previous output if there is pause i.e. no output from whisper
segments = self.get_previous_output()
if len(segments):
self.send_transcription_to_client(segments)
whisper_live/backend/trt_backend.py
+1 -3
View File
@@ -149,9 +149,7 @@ class ServeClientTensorRT(ServeClientBase):
If the client's language is not detected, it waits for 30 seconds of audio input to make a language prediction.
It utilizes the Whisper ASR model to transcribe the audio, continuously processing and streaming results. Segments
are sent to the client in real-time, and a history of segments is maintained to provide context.Pauses in speech
(no output from Whisper) are handled by showing the previous output for a set duration. A blank segment is added if
there is no speech for a specified duration to indicate a pause.
are sent to the client in real-time, and a history of segments is maintained to provide context.
Raises:
Exception: If there is an issue with audio processing or WebSocket communication.