sentence work again!

This commit is contained in:
Silas Kieser 2025-01-28 12:00:34 +01:00
parent 4622fe7aff
commit 870a779666

View file

@ -17,8 +17,10 @@ class HypothesisBuffer:
self.logfile = logfile
def insert(self, new, offset):
# compare self.commited_in_buffer and new. It inserts only the words in new that extend the commited_in_buffer, it means they are roughly behind last_commited_time and new in content
# the new tail is added to self.new
"""
compare self.commited_in_buffer and new. It inserts only the words in new that extend the commited_in_buffer, it means they are roughly behind last_commited_time and new in content
The new tail is added to self.new
"""
new = [(a + offset, b + offset, t) for a, b, t in new]
self.new = [(a, b, t) for a, b, t in new if a > self.last_commited_time - 0.1]
@ -77,6 +79,9 @@ class HypothesisBuffer:
return self.buffer
class OnlineASRProcessor:
SAMPLING_RATE = 16000
@ -128,7 +133,9 @@ class OnlineASRProcessor:
if offset is not None:
self.buffer_time_offset = offset
self.transcript_buffer.last_commited_time = self.buffer_time_offset
self.commited = []
self.final_transcript = []
self.commited_not_final = []
def insert_audio_chunk(self, audio):
self.audio_buffer = np.append(self.audio_buffer, audio)
@ -136,23 +143,42 @@ class OnlineASRProcessor:
def prompt(self):
"""Returns a tuple: (prompt, context), where "prompt" is a 200-character suffix of commited text that is inside of the scrolled away part of audio buffer.
"context" is the commited text that is inside the audio buffer. It is transcribed again and skipped. It is returned only for debugging and logging reasons.
"""
k = max(0, len(self.commited) - 1)
while k > 0 and self.commited[k - 1][1] > self.buffer_time_offset:
k -= 1
p = self.commited[:k]
p = [t for _, _, t in p]
prompt = []
l = 0
while p and l < 200: # 200 characters prompt size
x = p.pop(-1)
l += len(x) + 1
prompt.append(x)
non_prompt = self.commited[k:]
return self.asr.sep.join(prompt[::-1]), self.asr.sep.join(
t for _, _, t in non_prompt
)
"""
if len(self.final_transcript) == 0:
prompt=""
if len(self.final_transcript) == 1:
prompt = self.final_transcript[0][2][-200:]
else:
prompt = self.concatenate_tsw(self.final_transcript)[2][-200:]
# TODO: this is not ideal as we concatenate each time the whole transcript
# k = max(0, len(self.final_transcript) - 1)
# while k > 1 and self.final_transcript[k - 1][1] > self.buffer_time_offset:
# k -= 1
# p = self.final_transcript[:k]
# p = [t for _, _, t in p]
# prompt = []
# l = 0
# while p and l < 200: # 200 characters prompt size
# x = p.pop(-1)
# l += len(x) + 1
# prompt.append(x)
non_prompt = self.concatenate_tsw(self.commited_not_final)[2]
logger.debug(f"PROMPT(previous): {prompt[:20]}...{prompt[-20:]} (length={len(prompt)}chars)")
logger.debug(f"CONTEXT: {non_prompt}")
return prompt, non_prompt
def process_iter(self):
"""Runs on the current audio buffer.
@ -161,93 +187,111 @@ class OnlineASRProcessor:
"""
prompt, non_prompt = self.prompt()
logger.debug(f"PROMPT(previous): {prompt}")
logger.debug(f"CONTEXT: {non_prompt}")
logger.debug(
f"transcribing {len(self.audio_buffer)/self.SAMPLING_RATE:2.2f} seconds from {self.buffer_time_offset:2.2f}"
)
## Transcribe and format the result to [(beg,end,"word1"), ...]
res = self.asr.transcribe(self.audio_buffer, init_prompt=prompt)
# transform to [(beg,end,"word1"), ...]
tsw = self.asr.ts_words(res)
# insert into HypothesisBuffer
self.transcript_buffer.insert(tsw, self.buffer_time_offset)
o = self.transcript_buffer.flush()
# Completed words
self.commited.extend(o)
completed = self.concatenate_tsw(o) # This will be returned at the end of the function
logger.debug(f">>>>COMPLETE NOW: {completed[2]}")
## The rest is incomplete
the_rest = self.concatenate_tsw(self.transcript_buffer.complete())
logger.debug(f"INCOMPLETE: {the_rest[2]}")
# there is a newly confirmed text
# insert into HypothesisBuffer, and get back the commited words
self.transcript_buffer.insert(tsw, self.buffer_time_offset)
commited_tsw = self.transcript_buffer.flush()
if len(commited_tsw) == 0:
return (None, None, "")
self.commited_not_final.extend(commited_tsw)
# Define `completed` and `the_rest` based on the buffer_trimming_way
# completed will be returned at the end of the function.
# completed is a transcribed text with (beg,end,"sentence ...") format.
if self.buffer_trimming_way == "sentence":
self.chunk_completed_sentence(self.commited)
sentences = self.words_to_sentences(self.commited_not_final)
# TODO: new words in `completed` should not be reterned unless they form a sentence
# TODO: only complete sentences should go to completed
if len(self.audio_buffer) / self.SAMPLING_RATE > self.buffer_trimming_sec :
if len(sentences) < 2:
logger.debug(f"[Sentence-segmentation] no full sentence segmented, do not commit anything.")
if self.buffer_trimming_way == "sentence":
logger.warning(f"Chunck segment after {self.buffer_trimming_sec} seconds!"
" Even if no sentence was found!"
)
self.chunk_completed_segment(res)
completed = []
# alternative: on any word
# l = self.buffer_time_offset + len(self.audio_buffer)/self.SAMPLING_RATE - 10
# let's find commited word that is less
# k = len(self.commited)-1
# while k>0 and self.commited[k][1] > l:
# k -= 1
# t = self.commited[k][1]
# self.chunk_at(t)
else:
identified_sentence= "\n - ".join([f"{s[0]*1000:.0f}-{s[1]*1000:.0f} {s[2]}" for s in sentences])
logger.debug(f"[Sentence-segmentation] identified sentences:\n - {identified_sentence}")
# assume last sentence is incomplete, which is not always true
# we will continue with audio processing at this timestamp
chunk_at = sentences[-2][1]
self.chunk_at(chunk_at)
# TODO: here paragraph breaks can be added
self.commited_not_final = sentences[-1:]
completed= sentences[:-1]
else:
# break audio buffer anyway if it is too long
if len(self.audio_buffer) / self.SAMPLING_RATE > self.buffer_trimming_sec :
if self.buffer_trimming_way == "sentence":
logger.warning(f"Chunck segment after {self.buffer_trimming_sec} seconds!"
" Even if no sentence was found!"
)
completed = self.concatenate_tsw(self.commited_not_final)
self.commited_not_final = []
self.chunk_completed_segment(res)
# TODO: I don't know if res is the correct variable to pass here
else:
completed = []
return completed
def chunk_completed_sentence(self):
if self.commited == []:
return
raw_text = self.asr.sep.join([s[2] for s in self.commited])
logger.debug(f"COMPLETED SENTENCE: {raw_text}")
sents = self.words_to_sentences(self.commited)
if len(sents) < 2:
logger.debug(f"[Sentence-segmentation] no sentence segmented.")
return
if len(completed) == 0:
return (None, None, "")
else:
self.final_transcript.extend(completed) # add whole time stamped sentences / or words to commited list
identified_sentence= "\n - ".join([f"{s[0]*1000:.0f}-{s[1]*1000:.0f} {s[2]}" for s in sents])
logger.debug(f"[Sentence-segmentation] identified sentences:\n - {identified_sentence}")
# we will continue with audio processing at this timestamp
chunk_at = sents[-2][1]
completed_text_segment= self.concatenate_tsw(completed)
the_rest = self.concatenate_tsw(self.transcript_buffer.complete())
commited_but_not_final = self.concatenate_tsw(self.commited_not_final)
logger.debug(f"\n COMPLETE NOW: {completed_text_segment[2]}\n"
f" COMMITTED (but not Final): {commited_but_not_final[2]}\n"
f" INCOMPLETE: {the_rest[2]}"
)
self.chunk_at(chunk_at)
return completed_text_segment
def chunk_completed_segment(self, res):
if self.commited == []:
if self.final_transcript == []:
return
ends = self.asr.segments_end_ts(res)
t = self.commited[-1][1]
t = self.final_transcript[-1][1]
if len(ends) <= 1:
logger.debug(f"--- not enough segments to chunk (<=1 words)")
@ -287,9 +331,11 @@ class OnlineASRProcessor:
Returns: [(beg,end,"sentence 1"),...]
"""
cwords = [w for w in words]
t = self.asr.sep.join(o[2] for o in cwords)
logger.debug(f"[Sentence-segmentation] Raw Text: {t}")
s = self.tokenize([t])
out = []
while s:
@ -302,11 +348,13 @@ class OnlineASRProcessor:
w = w.strip()
if beg is None and sent.startswith(w):
beg = b
elif end is None and sent == w:
if end is None and sent == w:
end = e
if beg is not None and end is not None:
out.append((beg, end, fsent))
break
sent = sent[len(w) :].strip()
return out
def finish(self):
@ -330,7 +378,7 @@ class OnlineASRProcessor:
# return: (beg1,end-of-last-sentence,"concatenation of sentences") or (None, None, "") if empty
if sep is None:
sep = self.asr.sep
t = sep.join(s[2] for s in tsw)
if len(tsw) == 0:
b = None