Huawei Technologies Co., Limited

Signify Holding B.v.

Weiran Nie

Hai Yu

Youjia Huang

Jianfeng Wang

Saeed Reza Bagheri

Maulin Dahyabhai Patel

Sirisha Rangavajhala

Yi Gao

Yao-Jung Wen

Parikshit Shah

Zijuan Shi

Fuliang Weng

Shumang Hu

A speech detection method includes performing recognition on a photographed face image using a model to predict whether a user intends to continue speaking, and to determine whether a collected audio signal is a speech end point with reference to a prediction result.

Speech detection method, prediction model training method, apparatus, device, and medium

A speech recognition method, apparatus, and device, and a computer-readable storage medium provided pertain to the field of artificial intelligence technologies. The method includes: obtaining or generating a dynamic target language model based on reply information of a first intent, where the dynamic target language model includes a front-end part and a core part; obtaining a speech signal, parsing the speech signal to generate a key word; and invoking the dynamic target language model to determine a second intent and a service content. The front-end part of the dynamic target language model parses out the second intent based on the key word, and the core part of the dynamic target language model parses out the service content based on the key word. The speech recognition method prevents a provided service content from deviating from a user requirement and achieves a good recognition effect.

Speech recognition method, apparatus, and device, and computer-readable storage medium

A voice interaction method, where a service type set on which a user has a voice interaction intention is predicted based on a target event that can trigger voice interaction, and when a service type of a first service expressed by a voice instruction is a target service type in the service type set, the first service is executed.

Voice interaction method and apparatus, terminal, and storage medium

A filtering model training method includes obtaining N original syllables, obtaining N recognized syllables, and obtaining N syllable distances based on the N original syllables and the N recognized syllables, where the N syllable distances are in a one-to-one correspondence with N syllable pairs, the N original syllables and the N recognized syllables form the N syllable pairs, each syllable pair includes an original syllable and a recognized syllable that correspond to each other, and each syllable distance is used to indicate a similarity between an original syllable and a recognized syllable that are included in a corresponding syllable pair.

Filtering model training method and speech recognition method

A system and method for maintaining a system configuration to provide desired system performance is disclosed. The system comprises a processing unit receiving sensor data associated with environmental conditions within an area, generating a map of the area based on the received sensor data, determining a change in the map of the area and determining at least one system commissioning parameter associated with the determined change in the map to compensate for or correct the change in the map. In one aspect of the invention, the sensor data is provided through a plurality of mobile devices.

System and method for maintaining building automation system performance

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Shanghai, China

Weiran Nie