Baidu Online Network Technology (beijing) Co., Ltd.

Beijing Baidu Netcom Science and Technology Co., Ltd.

Xiaokong Ma

Chao Li

Lei Jia

Xiangang Li

Jinfeng Bai

Ce Zhang

Bing Jiang

Tao Chen

Xu Chen

Sheng Qian

Zhen Wu

Zhijian Wang

Guibin Wang

Xingyuan Peng

Chuanlei Zhai

Changbin Chen

Lin Zheng

Yujuan Sun

The present disclosure discloses an interactive voice-control method and apparatus, a device and a medium. The method includes: obtaining a sound signal at a voice interaction device and recognized information that is recognized from the sound signal; determining an interaction confidence of the sound signal based at least on at least one of an acoustic feature representation of the sound signal and a semantic feature representation associated with the recognized information; determining a matching status between the recognized information and the sound signal; and providing the interaction confidence and the matching status for controlling a response of the voice interaction device to the sound signal.

Interactive voice-control method and apparatus, device and medium

A method, apparatus, device, and storage medium for voice interaction. A specific embodiment of the method includes: extracting an acoustic feature from received voice data, the acoustic feature indicating a short-term amplitude spectrum characteristic of the voice data; applying the acoustic feature to a type recognition model to determine an intention type of the voice data, the intention type being one of an interaction intention type and a non-interaction intention type, and the type recognition model being constructed based on the acoustic feature of training voice data; and performing an interaction operation indicated by the voice data, based on determining that the intention type is the interaction intention type.

Method and apparatus for voice interaction, device and computer-readable storage medium

A method and apparatus of training an acoustic feature extracting model, a device and a computer storage medium. The method comprises: considering a first acoustic feature extracted respectively from speech data corresponding to user identifiers as training data; training an initial model based on a deep neural network based on a criterion of a minimum classification error, until a preset first stop condition is reached; using a triplet loss layer to replace a Softmax layer in the initial model to constitute an acoustic feature extracting model, and continuing to train the acoustic feature extracting model until a preset second stop condition is reached, the acoustic feature extracting model being used to output a second acoustic feature of the speech data; wherein the triplet loss layer is used to maximize similarity between the second acoustic features of the same user, and minimize similarity between the second acoustic features of different users.

Method and apparatus of training acoustic feature extracting model, device and computer storage medium

A method and apparatus of building an acoustic feature extracting model, and an acoustic feature extracting method and apparatus. The method of building an acoustic feature extracting model comprises: considering first acoustic features extracted respectively from speech data corresponding to user identifiers as training data; using the training data to train a deep neural network to obtain an acoustic feature extracting model; wherein a target of training the deep neural network is to maximize similarity between the same user's second acoustic features and minimize similarity between different users' second acoustic features. The acoustic feature extracting model according to the present disclosure can self-learn optimal acoustic features that achieves a training target. As compared with a conventional acoustic feature extracting manner with a preset feature type and transformation manner, the acoustic feature extracting manner of the present disclosure achieves better flexibility and higher accuracy.

Method and apparatus of building acoustic feature extracting model, and acoustic feature extracting method and apparatus

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Beijing, China

Xiaokong Ma