Update README.md
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README.md
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@@ -43,7 +43,7 @@ tacotron2 = Tacotron2.from_hparams(source="speechbrain/tts-tacotron2-ljspeech",
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hifi_gan = HIFIGAN.from_hparams(source="speechbrain/tts-hifigan-ljspeech", savedir="tmpdir_vocoder")
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# Running the TTS
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mel_output, mel_length, alignment = tacotron2.encode_text("
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# Running Vocoder (spectrogram-to-waveform)
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waveforms = hifi_gan.decode_batch(mel_output)
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@@ -57,10 +57,11 @@ If you want to generate multiple sentences in one-shot, you can do in this way:
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```
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from speechbrain.pretrained import Tacotron2
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tacotron2 = Tacotron2.from_hparams(source="speechbrain/TTS_Tacotron2", savedir="tmpdir")
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items = [
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"
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"
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"
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]
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mel_outputs, mel_lengths, alignments = tacotron2.encode_batch(items)
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hifi_gan = HIFIGAN.from_hparams(source="speechbrain/tts-hifigan-ljspeech", savedir="tmpdir_vocoder")
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# Running the TTS
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mel_output, mel_length, alignment = tacotron2.encode_text("Mbagaliza Christmass Enungi Nomwaka Omugya Gubaberere Gwamirembe")
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# Running Vocoder (spectrogram-to-waveform)
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waveforms = hifi_gan.decode_batch(mel_output)
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```
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from speechbrain.pretrained import Tacotron2
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tacotron2 = Tacotron2.from_hparams(source="speechbrain/TTS_Tacotron2", savedir="tmpdir")
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items = [
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"Nsanyuse okukulaba",
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"Erinnya lyo ggwe ani?",
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"Mbagaliza Christmass Enungi Nomwaka Omugya Gubaberere Gwamirembe"
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]
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mel_outputs, mel_lengths, alignments = tacotron2.encode_batch(items)
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