sentence work again!

src/whisper_streaming/online_asr.py

@@ -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
+        if len(self.final_transcript) == 0:
-        while p and l < 200:  # 200 characters prompt size
+            prompt=""
-            x = p.pop(-1)
+
-            l += len(x) + 1
+        if len(self.final_transcript) == 1:
-            prompt.append(x)
+            prompt = self.final_transcript[0][2][-200:]
-        non_prompt = self.commited[k:]
+        
-        return self.asr.sep.join(prompt[::-1]), self.asr.sep.join(
+        else:
-            t for _, _, t in non_prompt
+            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":
+                completed = []
-                logger.warning(f"Chunck segment after {self.buffer_trimming_sec} seconds!"
-                                " Even if no sentence was found!"
-                             )
-            
-            
-            self.chunk_completed_segment(res)
-    
-       
 
-                # alternative: on any word
+            
-                # l = self.buffer_time_offset + len(self.audio_buffer)/self.SAMPLING_RATE - 10
+            else:
-                # let's find commited word that is less
+                identified_sentence= "\n    - ".join([f"{s[0]*1000:.0f}-{s[1]*1000:.0f} {s[2]}" for s in sentences])
-                # k = len(self.commited)-1
+                logger.debug(f"[Sentence-segmentation] identified sentences:\n    - {identified_sentence}")
-                # while k>0 and self.commited[k][1] > l:
+
-                #    k -= 1
+                # assume last sentence is incomplete, which is not always true
-                # t = self.commited[k][1]
+
-                # self.chunk_at(t)
+                # 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 len(completed) == 0:      
-        if self.commited == []:
+            return (None, None, "")
-            return        
+        else:
-        raw_text = self.asr.sep.join([s[2] for s in self.commited]) 
+            self.final_transcript.extend(completed) # add whole time stamped sentences / or words to commited list
-        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
         
 
-
+            completed_text_segment= self.concatenate_tsw(completed)
-        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}")
+            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"
-        # we will continue with audio processing at this timestamp
+                         f"    COMMITTED (but not Final): {commited_but_not_final[2]}\n"
-        chunk_at = sents[-2][1]
+                         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