diff options
Diffstat (limited to 'transcribe.py')
| -rw-r--r-- | transcribe.py | 49 |
1 files changed, 9 insertions, 40 deletions
diff --git a/transcribe.py b/transcribe.py index 99429c6..474cd59 100644 --- a/transcribe.py +++ b/transcribe.py @@ -2,8 +2,7 @@ import argparse import copy -# python3 -m pip install python-Levenshtein -from Levenshtein import distance as levenshtein_distance +import string_matcher import os import osc_ctrl # python3 -m pip install pydub @@ -212,7 +211,7 @@ def transcribeAudio(audio_state, model): continue words = ''.join(c for c in text.lower() if (c.isalpha() or c == " ")).split() - print("words: {}".format(words)) + #print("words: {}".format(words)) if len(words) > 0 and words[-1] == "clear": audio_state.text = "" audio_state.text_candidate = "" @@ -229,7 +228,7 @@ def transcribeAudio(audio_state, model): # immediately accept it, since the transcription is obviously # somewhat stable. # 3. If the transcription is somewhat long and the - # first few characters change, we assume this is due to a + # first few words change, we assume this is due to a # trim event and immediately accept the transcription. candidate_words = ''.join(c for c in audio_state.text_candidate.lower() if (c.isalpha() or c == " ")).split() @@ -241,47 +240,17 @@ def transcribeAudio(audio_state, model): commit_transcription = False if words == candidate_words or candidate_words_are_prefix_of_text: commit_transcription = True - elif len(text) > 30 and len(audio_state.text_candidate) >= 10: - d = levenshtein_distance(text[0:10], - audio_state.text_candidate[0:10]) - if d > 2: - commit_transcription = True + elif len(words) >= 3 and len(candidate_words) >= 3 and \ + words[0:3] != candidate_words[0:3]: + commit_transcription = True print("Transcription: {}".format(audio_state.text)) if commit_transcription: - window_size = 20 old_text = audio_state.text - if audio_state.text == text: - pass - elif len(text) >= window_size and len(old_text) >= window_size: - old_slice = old_text[len(old_text) - window_size:] - best_match_i = None - best_match_d = window_size * 1000 - for i in range(0, 1 + len(text) - window_size): - new_slice = text[i:i + window_size] - #print("Consider slice {}".format(new_slice)) - d = levenshtein_distance(old_slice, new_slice) - if d < best_match_d and d < window_size: - best_match_i = i - best_match_d = d - if best_match_i == None: - audio_state.text = text - else: - #print("Best overlap: {}, {}".format(best_match_d, text[best_match_i:best_match_i + window_size])) - #print("Old prefix: {}".format(old_text[0:len(old_text) - window_size])) - #print("New suffix: {}".format(text[best_match_i:])) - new_text = old_text[0:len(old_text) - window_size] - new_text += text[best_match_i:] - audio_state.text = new_text - else: - audio_state.text = text - - if audio_state.text != old_text: - # We think the user said something, so reset the amount of - # time we sleep between transcriptions to the minimum. - audio_state.transcribe_no_change_count = 0 - audio_state.transcribe_sleep_duration = audio_state.transcribe_sleep_duration_min_s + old_words = audio_state.text.split() + new_words = text.split() + audio_state.text = string_matcher.matchStringList(old_words, new_words) audio_state.text_candidate = text |