MultiSpeech: Multi-Speaker Text to Speech with Transformer
Table 1: The MOS scores with 95% confidence intervals on VCTK and LibriTTS.
['[BOLD] Setting', '[BOLD] VCTK', '[BOLD] LibriTTS']
We compare our proposed MultiSpeech with 1) GT, the ground-truth recording, 2) GT mel + Vocoder, we first convert the recording into mel-spectrogram and then convert the mel-spectrogram back to audio with Vocoder, and 3) Transformer based TTS , we only add the speaker embedding module on naive Transformer based TTS model to support multiple speakers, without using any of our proposed techniques to improve alignments. It can be seen that MultiSpeech achieves large MOS score improvements over Transformer based TTS. Transformer based TTS cannot learn effective alignments on most sentences and causes word skipping and repeating issues, or totally crashed voice. The MOS score of MultiSpeech on VCTK is also close to GT mel + Vocoder. These results demonstrate the advantages of MultiSpeech for multi-speaker TTS.