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“Practically all the systems work well at the sentence level,” says Alex Acero, senior director of Siri at Apple. Ask a machine to read you a newspaper article or an email message from your mother, however, and the result will be flat. “Yes, you can understand it if you pay attention, but it’s still not the same

MACHINES THAT SPEAK are nothing new. Siri has been answering ques- tions from iPhone users ince 2011, and text-to-voice programs have been around even longer. People with speaking disabilities—most famously, Stephen Hawking—have used computers to generate speech for decades. Yet synthesizing speech that sounds as natural as if spoken by a human is still an elusive goal, although one that appears to be getting closer to reality.

If you listen to the latest version of Apple’s Siri, “it sounds pretty amazing,” says Simon King, a professor of speech processing and director of the Centre for Speech Technology Research at the University of Edinburgh. Apple, Google, and Microsoft all have commercial speech applications that read text in a neutral but reasonable-sounding tone. Words are pronounced correctly, for the most part, and generally flow from one to the next in perfectly acceptable sentences. “We’re quite good at that and the speech is very intelligible,” King says.

Researchers in speech synthesis,
however, would like to move beyond
merely “intelligible” to speech that
sounds more natural. Their work
could make synthesized speech eas-
ier to understand and more pleasant
to hear. It could also allow them to
synthesize better voices for people
unable to speak for themselves, and
create text-to-speech systems for less-
common languages.
Thinking Deeply to
Make Better Speech

More work is needed to make synthesized speech more natural, easier to understand, and more pleasant to hear.

Science | DOI: 10.1145/3037384 Neil Savage

A humanoid robot, named Aiko Chihira by its creators at Toshiba and Osaka University, at a 2015 trial in Tokyo’s Mitsukoshi department store. Toshiba says it will incorporate speech recognition and synthesis into the robot by 2020.