--- tags: - tensorflowtts - audio - text-to-speech - text-to-mel language: eng license: apache-2.0 datasets: - LJSpeech widget: - text: "How are you?" --- # FastSpeech trained on LJSpeech (Eng) This repository provides a pretrained [FastSpeech](https://arxiv.org/abs/1905.09263) trained on LJSpeech dataset (ENG). For a detail of the model, we encourage you to read more about [TensorFlowTTS](https://github.com/TensorSpeech/TensorFlowTTS). ## Install TensorFlowTTS First of all, please install TensorFlowTTS with the following command: ``` pip install TensorFlowTTS ``` ### Converting your Text to Mel Spectrogram ```python import numpy as np import soundfile as sf import yaml import tensorflow as tf from tensorflow_tts.inference import AutoProcessor from tensorflow_tts.inference import TFAutoModel processor = AutoProcessor.from_pretrained("tensorspeech/tts-fastspeech-ljspeech-en") fastspeech = TFAutoModel.from_pretrained("tensorspeech/tts-fastspeech-ljspeech-en") text = "How are you?" input_ids = processor.text_to_sequence(text) mel_before, mel_after, duration_outputs = fastspeech.inference( input_ids=tf.expand_dims(tf.convert_to_tensor(input_ids, dtype=tf.int32), 0), speaker_ids=tf.convert_to_tensor([0], dtype=tf.int32), speed_ratios=tf.convert_to_tensor([1.0], dtype=tf.float32), ) ``` #### Referencing FastSpeech ``` @article{DBLP:journals/corr/abs-1905-09263, author = {Yi Ren and Yangjun Ruan and Xu Tan and Tao Qin and Sheng Zhao and Zhou Zhao and Tie{-}Yan Liu}, title = {FastSpeech: Fast, Robust and Controllable Text to Speech}, journal = {CoRR}, volume = {abs/1905.09263}, year = {2019}, url = {http://arxiv.org/abs/1905.09263}, archivePrefix = {arXiv}, eprint = {1905.09263}, timestamp = {Wed, 11 Nov 2020 08:48:07 +0100}, biburl = {https://dblp.org/rec/journals/corr/abs-1905-09263.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } ``` #### Referencing TensorFlowTTS ``` @misc{TFTTS, author = {Minh Nguyen, Alejandro Miguel Velasquez, Erogol, Kuan Chen, Dawid Kobus, Takuya Ebata, Trinh Le and Yunchao He}, title = {TensorflowTTS}, year = {2020}, publisher = {GitHub}, journal = {GitHub repository}, howpublished = {\\url{https://github.com/TensorSpeech/TensorFlowTTS}}, } ```