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Abstract / Description of output
We introduce the Merlin speech synthesis toolkit for neural network-based speech synthesis. The system takes linguistic features as input, and employs neural networks to predict acoustic features, which are then passed to a vocoder to produce the speech waveform. Various neural netw are implemented, including a standard feedforward neural network, mixture density neural network, recurrent neural network (RNN), long short-term memory (LSTM) recurrent neural network, amongst others. The toolkit is Open Source, written in Python, and is extensible. This paper briefly describes the system, and provides some benchmarking results on a freely available corpus.
Original language | English |
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Title of host publication | 9th ISCA Speech Synthesis Workshop (2016) |
Pages | 202-207 |
Number of pages | 6 |
DOIs | |
Publication status | Published - 15 Sept 2016 |
Event | 9th ISCA Speech Synthesis Workshop - Sunnyvale, United States Duration: 13 Sept 2016 → 15 Sept 2016 http://ssw9.talp.cat/ |
Conference
Conference | 9th ISCA Speech Synthesis Workshop |
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Abbreviated title | ISCA 2016 |
Country/Territory | United States |
City | Sunnyvale |
Period | 13/09/16 → 15/09/16 |
Internet address |
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