Audio Sample

The main processes of TTS include:

  1. Convert the original text into characters/phonemes, through text frontend module.

  2. Convert characters/phonemes into acoustic features , such as linear spectrogram, mel spectrogram, LPC features, etc. through Acoustic models.

  3. Convert acoustic features into waveforms through Vocoders.

When training Tacotron2TransformerTTS and WaveFlow, we use English single speaker TTS dataset LJSpeech by default. However, when training SpeedySpeech, FastSpeech2 and ParallelWaveGAN, we use Chinese single speaker dataset CSMSC by default.

In the future, PaddleSpeech TTS will mainly use Chinese TTS datasets for default examples.

Here, we will display three types of audio samples:

  1. Analysis/synthesis (ground-truth spectrograms + Vocoder)

  2. TTS (Acoustic model + Vocoder)

  3. Chinese TTS with/without text frontend (mainly tone sandhi)

Analysis/synthesis

Audio samples generated from ground-truth spectrograms with a vocoder.

LJSpeech(English)

Text GT WaveFlow
Printing, in the only sense with which we are at present concerned, differs from most if not from all the arts and crafts represented in the Exhibition
in being comparatively modern.
For although the Chinese took impressions from wood blocks engraved in relief for centuries before the woodcutters of the Netherlands, by a similar process
produced the block books, which were the immediate predecessors of the true printed book
the invention of movable metal letters in the middle of the fifteenth century may justly be considered as the invention of the art of printing.


CSMSC(Chinese)

Text GT (convert to 24k) ParallelWaveGAN
昨日,这名“伤者”与医生全部被警方依法刑事拘留
钱伟长想到上海来办学校是经过深思熟虑的。
她见我一进门就骂,吃饭时也骂,骂得我抬不起头。
李述德在离开之前,只说了一句“柱驼杀父亲了”
这种车票和保险单捆绑出售属于重复性购买。


TTS

Audio samples generated by a TTS system. Text is first transformed into spectrogram by a text-to-spectrogram model, then the spectrogram is converted into raw audio by a vocoder.

LJSpeech(English)

Text TransformerTTS + WaveFlow Tacotron2 + WaveFlow
Life was like a box of chocolates, you never know what you're gonna get.
With great power there must come great responsibility.
To be or not to be, that’s a question.
A man can be destroyed but not defeated.
Do not, for one repulse, give up the purpose that you resolved to effort.
Death is just a part of life, something we're all destined to do.
I think it's hard winning a war with words.
Don’t argue with the people of strong determination, because they may change the fact!
Love you three thousand times.


CSMSC(Chinese)

Text SpeedySpeech + ParallelWaveGAN FastSpeech2 + ParallelWaveGAN
凯莫瑞安联合体的经济崩溃,迫在眉睫。
对于所有想要离开那片废土,去寻找更美好生活的人来说。
克哈,是你们所有人安全的港湾。
为了保护尤摩扬人民不受异虫的残害,我所做的,比他们自己的领导委员会都多。
无论他们如何诽谤我,我将继续为所有泰伦人的最大利益,而努力奋斗。
身为你们的元首,我带领泰伦人实现了人类统治领地和经济的扩张。
我们将继续成长,用行动回击那些只会说风凉话,不愿意和我们相向而行的害群之马。
帝国武装力量,无数的优秀儿女,正时刻守卫着我们的家园大门,但是他们孤木难支。
凡是今天应征入伍者,所获的所有刑罚罪责,减半。


FastSpeech2-Conformer + ParallelWaveGAN


Multi-Speaker TTS

PaddleSpeech also support Multi-Speaker TTS, we provide the audio demos generated by FastSpeech2 + ParallelWaveGAN, we use AISHELL-3 Multi-Speaker TTS dataset. Each line is a different person.

Target Timbre Generated


Style control in FastSpeech2

In our FastSpeech2, we can control duration, pitch and energy.

We provide the audio demos of duration control here. duration means the duration of phonemes, when we reduce duration, the speed of audios will increase, and when we incerase duration, the speed of audios will reduce.

The duration of different phonemes in a sentence can have different scale ratios (when you want to slow down one word and keep the other words' speed in a sentence). Here we use a fixed scale ratio for different phonemes to control the speed of audios.

The duration control in FastSpeech2 can control the speed of audios will keep the pitch. (in some speech tool, increase the speed will increase the pitch, and vice versa.)

Speed(0.8x) Speed(1x) Speed(1.2x)


We provide the audio demos of pitch control here.

When we set pitch of one sentence to a mean value and set tones of phones to 1, we will get a robot-style timbre.

When we raise the pitch of an adult female (with a fixed scale ratio), we will get a child-style timbre.

The pitch of different phonemes in a sentence can also have different scale ratios.

The nomal audios are in the second column of the previous table.

Robot Child


Chinese TTS with/without text frontend

We provide a complete Chinese text frontend module in PaddleSpeech TTS. Text Normalization and G2P are the most important modules in text frontend, We assume that the texts are normalized already, and mainly compare G2P module here.

We use FastSpeech2 + ParallelWaveGAN here.

Text With Text Frontend Without Text Frontend
他只是一个纸老虎。
手表厂有五种好产品。
老板的轿车需要保养。
我们所有人都好喜欢你呀。
岂有此理。
虎骨酒多少钱一瓶。
这件事情需要冷处理。
这个老奶奶是个大喇叭。
我喜欢说相声。
有一天,我路过了一栋楼。


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