Researchers have begun to use deep learning techniques for language modeling as well.In the long history of speech recognition, both shallow form and deep form (e.g. This innovation was quickly adopted across the field. In contrast to the steady incremental improvements of the past few decades, the application of deep learning decreased word error rate by 30%. A Microsoft research executive called this innovation 'the most dramatic change in accuracy since 1979'. In 2015, Google's speech recognition reportedly experienced a dramatic performance jump of 49% through CTC-trained LSTM, which is now available through to all smartphone users.The use of deep feedforward (non-recurrent) networks for was introduced during later part of 2009 by and his students at University of Toronto and by Li Deng and colleagues at Microsoft Research, initially in the collaborative work between Microsoft and University of Toronto which was subsequently expanded to include IBM and Google (hence 'The shared views of four research groups' subtitle in their 2012 review paper). ) This was controversial with linguists since HMMs are too simplistic to account for many common features of human languages. (Jelinek's group independently discovered the application of HMMs to speech.

By the mid-1980s IBM's team created a voice activated typewriter called Tangora, which could handle a 20,000-word vocabulary Jelinek's statistical approach put less emphasis on emulating the way the human brain processes and understands speech in favor of using statistical modeling techniques like HMMs. The use of HMMs allowed researchers to combine different sources of knowledge, such as acoustics, language, and syntax, in a unified probabilistic model.

James Baker had learned about HMMs from a summer job at the Institute of Defense Analysis during his undergraduate education. A decade later, at CMU, Raj Reddy's students and began using the (HMM) for speech recognition. 1976 The first was held in, which since then has been a major venue for the publication of research on speech recognition.During the late 1960s developed the mathematics of at the.

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