Very poor performance on my own wav file, is there anything wrong? about speaker-diarization HOT 2 OPEN

Is your own wav file in English or Chinese? I had a look at the wav file in this repo, it seems like the models were trained in Mandarin. Hence the results were bad on my English wav files.

from speaker-diarization.

Thanks to Shuning, I verified on Mandarin wave files too, and I just check the sample result provided in this project, it seems not very good too. I use following code to split wave file:

sound = AudioSegment.from_file(wav_path)
for spk,timeDicts in speakerSlice.items():
    print('========= ' + str(spk) + ' =========')
    index = 0
    for timeDict in timeDicts:
        s = timeDict['start']
        e = timeDict['stop']
        seg = sound[s:e]
        seg.export("wavs/rmd/" + str(spk) + "/seg_%d.wav" % index, format="wav")
        index = index + 1

from speaker-diarization.