Oh no, you're thinking, yet another cookie pop-up. Well, sorry, it's the law. We measure how many people read us, and ensure you see relevant ads, by storing cookies on your device. If you're cool with that, hit “Accept all Cookies”. For more info and to customize your settings, hit “Customize Settings”.

Review and manage your consent

Here's an overview of our use of cookies, similar technologies and how to manage them. You can also change your choices at any time, by hitting the “Your Consent Options” link on the site's footer.

Manage Cookie Preferences
  • These cookies are strictly necessary so that you can navigate the site as normal and use all features. Without these cookies we cannot provide you with the service that you expect.

  • These cookies are used to make advertising messages more relevant to you. They perform functions like preventing the same ad from continuously reappearing, ensuring that ads are properly displayed for advertisers, and in some cases selecting advertisements that are based on your interests.

  • These cookies collect information in aggregate form to help us understand how our websites are being used. They allow us to count visits and traffic sources so that we can measure and improve the performance of our sites. If people say no to these cookies, we do not know how many people have visited and we cannot monitor performance.

See also our Cookie policy and Privacy policy.

This article is more than 1 year old

Google's AI finds its voice ... and it's surprisingly human

Talk like a robot? I'm sorry Dave, I'm afraid I can do that

Google has figured out how to use artificial intelligence to make robot sounds more human, according to a new paper.

Using its “WaveNet” model, Google’s AI company in the UK, DeepMind, claims to have created a natural machine-to-human speech that halves “the gap with human performance."

Machine babble often sounds emotionally flat and robotic because it’s difficult to capture the natural nuances of human speech.

Many systems are still based on a method called “concatenative text-to-speech” (TTS), which sounds out words by stringing together a large collection of phonetic sounds.

Researchers have managed to improve speech synthesis a bit by using “parametric text-to-speech,” which uses a vocoder – a device that employs a set of algorithms to process sounds from speech.

Although parametric TTS is more complex than concatenative TTS, the result can be even worse for syllabic languages like English, according to Google.

Like many existing AI projects, DeepMind has turned to using neural networks – a system modelled on how the human brain works – capable of processing huge heaps of data to perform a specific task.

WaveNet directly models the “raw waveform of the audio signal, one sample at a time.” It requires high computing power, because raw audio produces about 16,000 samples per second at many time scales.

The neural network is trained by recording human speech. As the sounds are sampled, a value is “drawn from a probability distribution computed by the network.” The value is then pumped back into the input and the system has to predict the next step for each sample. Building up these samples from a wider range of human voices makes the result more realistic.

Google DeepMind claims that using WaveNet in US English and Mandarin Chinese has closed the gap between human and AI speech by 50 per cent, according to mean opinion scores calculated by subjective evaluation.

After training, to transform text to speech, WaveNet has to first process the text. The words in the text are unscrambled into a “sequence of linguistic and phonetic features” that feeds into the neural network.

Training WaveNets without text results in gibberish. The AI system has to make it up as it goes along, stringing together human-sounding noises that don’t make any sense.

In DeepMind’s blog post, it hasn’t said how this technology will be applied. But the team has used it to produce AI-made piano music. You can hear how the AI speaks and makes music here. ®

Similar topics

TIP US OFF

Send us news


Other stories you might like