​Google voice search now faster and works in noisy places

25 Sep 2015 | Author: | No comments yet »

Google improves voice search (again) for its mobile apps.

Google GOOG 0.55% is claiming better voice search on its Android and iOS mobile apps, thanks to a new approach to the artificial intelligence technique the company uses to power that capability.

PanARMENIAN.Net – Google’s voice search has become more accurate, thanks to advances in artificial intelligence, the tech company announced Thursday, September 25, VentureBeat reports. “We are happy to announce we built even better neural network acoustic models using Connectionist Temporal Classification (CTC) and sequence discriminative training techniques,” Google Speech Team members Haşim Sak, Andrew Senior, Kanishka Rao, Françoise Beaufays and Johan Schalkwyk wrote in a blog post today. “These models are a special extension of recurrent neural networks (RNNs) that are more accurate, especially in noisy environments, and they are blazingly fast!” The new models are working in the Google app for iOS and Android, as well as dictation on Android, which works inside of some third-party apps, the team members wrote. In the old model, the system would analyze 10-millisecond snippets of audio and make predictions of words based on the sounds it recognized, regardless of the order in which they were uttered. RNNs are one increasingly popular approach to doing deep learning, a type of artificial intelligence, and Google is widely thought to have a deep bench in deep learning. For example, the word “museum” is broken up into / m j u z i @ m/ in phonetic notation and normally the sounds made by “j” and “u” would be difficult to separate.

RNNs have feedback loops in their topology, allowing them to model temporal dependencies: when the user speaks /u/ in the previous example, their articulatory apparatus is coming from a /j/ sound and from an /m/ sound before. Google’s voice recognition team also added ambient noise and reverb to the the data it used to train its new system, meaning it does a better job understanding users trying to talk to their phones while in noisy places.

It’s all very complicated stuff from a computer science perspective, but is increasingly important to our everyday lives as we expect everything from our phones to our cars to be more intelligent. You’ll get to keep your current user name (as long as it doesn’t contain invalid characters, in which case you’ll have to go through a few extra steps to make the transfer), and all your old comments will eventually (not immediately) migrate with you. If you want to learn more about how deep learning, the umbrella term for this collection of techniques, works, read Fortune‘s recent interview with Andrew Ng, the chief scientist at Chinese search engine giant Baidu BIDU 0.17% and a renowned expert in the space.

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