Updating the base directory

README.md

@@ -178,10 +178,12 @@ Here is a non exhaustive list of open-source projects using faster-whisper. Feel
 
 * [whisper-ctranslate2](https:/Softcatala/whisper-ctranslate2) is a command line client based on faster-whisper and compatible with the original client from openai/whisper.
 * [whisper-diarize](https:/MahmoudAshraf97/whisper-diarization) is a speaker diarization tool that is based on faster-whisper and NVIDIA NeMo.
-* [whisper-standalone-win](https:/Purfview/whisper-standalone-win) contains the portable ready to run binaries of faster-whisper for Windows.
+* [whisper-standalone-win](https:/Purfview/whisper-standalone-win) Standalone CLI executables of faster-whisper for Windows, Linux & macOS. 
 * [asr-sd-pipeline](https:/hedrergudene/asr-sd-pipeline) provides a scalable, modular, end to end multi-speaker speech to text solution implemented using AzureML pipelines.
 * [Open-Lyrics](https:/zh-plus/Open-Lyrics) is a Python library that transcribes voice files using faster-whisper, and translates/polishes the resulting text into `.lrc` files in the desired language using OpenAI-GPT.
 * [wscribe](https:/geekodour/wscribe) is a flexible transcript generation tool supporting faster-whisper, it can export word level transcript and the exported transcript then can be edited with [wscribe-editor](https:/geekodour/wscribe-editor)
+* [aTrain](https:/BANDAS-Center/aTrain) is a graphical user interface implementation of faster-whisper developed at the BANDAS-Center at the University of Graz for transcription and diarization in Windows ([Windows Store App](https://apps.microsoft.com/detail/atrain/9N15Q44SZNS2)) and Linux.
+* [WhisperLive](https:/collabora/WhisperLive) is a nearly-live implementation of OpenAI's Whisper which uses faster-whisper as the backend to transcribe audio in real-time.
 
 ## Model conversion
 

faster_whisper/transcribe.py

@@ -731,6 +731,13 @@ def generate_with_fallback(
  decode_result = max(
  below_cr_threshold_results or all_results, key=lambda x: x[1]
  )
+ # to pass final temperature for prompt_reset_on_temperature
+ decode_result = (
+ decode_result[0],
+ decode_result[1],
+ temperature,
+ decode_result[3],
+ )
 
  return decode_result
 
@@ -908,6 +915,13 @@ def find_alignment(
  words, word_tokens = tokenizer.split_to_word_tokens(
  text_tokens + [tokenizer.eot]
  )
+ if len(word_tokens) <= 1:
+ # return on eot only
+ # >>> np.pad([], (1, 0))
+ # array([0.])
+ # This results in crashes when we lookup jump_times with float, like
+ # IndexError: arrays used as indices must be of integer (or boolean) type
+ return []
  word_boundaries = np.pad(np.cumsum([len(t) for t in word_tokens[:-1]]), (1, 0))
  if len(word_boundaries) <= 1:
  return []