Add speaker-aware transcription

[juanmc2005]

Depends on #144

This PR adds a new SpeakerAwareTranscription pipeline that combines streaming diarization and streaming transcription to determine "who says what" in a live conversation. By default, this is shown as colored words in the terminal.

The feature works as expected with diart.stream and diart.serve/diart.client.
The main thing preventing full compatibility with diart.benchmark and diart.tune is the evaluation metric.
Since the output of the pipeline is annotated text with the format: [speaker0]Hello [speaker1]Hi, the metric diart.metrics.WordErrorRate will count labels as insertion errors.

Next steps: implement a SpeakerWordErrorRate that computes the (weighted?) average WER across speakers.

Changelog

TBD

[C0RE1312]

Hey, I am unable to use this:
(diart) :~/live-transcript$ diart.stream output.wav --pipeline SpeakerAwareTranscription
Traceback (most recent call last):
File "/home/user/anaconda3/envs/diart/lib/python3.8/site-packages/rx/core/operators/map.py", line 37, in on_next
result = _mapper(value)
File "/home/user/anaconda3/envs/diart/lib/python3.8/site-packages/diart/pipelines/speaker_transcription.py", line 325, in call
asr_outputs = self.asr(batch[has_voice])
File "/home/user/anaconda3/envs/diart/lib/python3.8/site-packages/diart/blocks/asr.py", line 65, in call
output = self.model(wave.to(self.device))
File "/home/user/anaconda3/envs/diart/lib/python3.8/site-packages/diart/models.py", line 80, in call
return super().call(*args, **kwargs)
File "/home/user/anaconda3/envs/diart/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "/home/user/anaconda3/envs/diart/lib/python3.8/site-packages/diart/models.py", line 485, in forward
batch = whisper.log_mel_spectrogram(batch)
File "/home/user/anaconda3/envs/diart/lib/python3.8/site-packages/whisper/audio.py", line 148, in log_mel_spectrogram
stft = torch.stft(audio, N_FFT, HOP_LENGTH, window=window, return_complex=True)
File "/home/user/anaconda3/envs/diart/lib/python3.8/site-packages/torch/functional.py", line 632, in stft
return _VF.stft(input, n_fft, hop_length, win_length, window, # type: ignore[attr-defined]
RuntimeError: cuFFT error: CUFFT_INTERNAL_ERROR

[juanmc2005]

@C0RE1312 sounds like a problem with pytorch not being able to compute the FFT. Have you tried updating the dependenciesof both torch and whisper? it's a pretty old PR