While a typical academic project uses 2,000 hours of audio data to train voice recognition,says Mr Ng, the troves of data available to China’s version of Google mean he is able to use100,000 hours.
吴恩达说,一个典型的学术项目会利用2000小时的音频数据来训练语音识别,但百度——中国版谷歌——拥有的庞大数据库意味着他可以利用10万小时。
He declines to specify just how much the extra 98,000 hours improves the accuracy of hisproject, but insists it is vital.
他拒绝详细说明额外9.8万小时在多大程度上提升了其项目的精确度,但坚称这至关重要。
“A lot of people underestimate the difference between 95 per cent and 99 per cent accuracy.It’s not an ‘incremental’ improvement of 4 per cent; it’s the difference between using itoccasionally versus using it all the time, he says.
“许多人低估了95%精确度与99%精确度之间的区别。这不是4%的“增量提升;这是偶尔使用与始终使用之间的区别,他说。
Thanks to the strides made in Chinese language voice recognition — a particular challengebecause of the number of homonyms and the importance of context — Baidu will soon roll outDeepspeech, a voice recognition software similar to Apple’s Siri.
由于在汉语语音识别方面取得了巨大进步(汉语中的大量同音异义词和语境的重要性使之极具挑战),百度即将推出Deepspeech——一款类似于苹果(Apple)的Siri的语音识别软件。
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