Update README.md

README.md

@@ -5,9 +5,13 @@ language:
 - en
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-A diarization pipeline for Whisper large-v2 that uses a custom-tuned segmentation model and custom filtering on the audio (low-pass filter, equalizer, etc.) for improved performance. 
+A Japanese transcription/diarization pipeline with Pyannote and Whisper large-v2 that uses a custom-tuned segmentation model and custom filtering on the audio (low-pass filter, equalizer, etc.) for improved performance. 
 Can be given a video file or mp3/wav file.  
 
-Performance is considerably better than default JP whisper for most tasks involving Japanese content, with the exception of singing/karaoke.
+Performance is considerably better than default JP whisper for most tasks involving Japanese content, with the exception of singing/karaoke (Where performance is below the origin.
+
+Requires ffmpeg, openai-whisper, pyannote and facebookresearch's demux model. Torch is also strongly encouraged. 
+Pyannote requies a Huggingface API key, which it will currently look for under the environment variable "HF_TOKEN_NOT_LOGIN" (At the time of this writing, naming your HF token "HF_TOKEN" causes bugs.)
+
+Originally intended as a solo project, but I'm upping it here in the hopes it will be useful to practicioners. If you're doing work in this space please feel free to reach out.
 
-Requires ffmpeg, pyannote and facebookresearch's demux model. Torch is also strongly encouraged.