Tencent Technology (shenzhen) Company Limited

Tencent Technology Company Limited

Dadong Xie

Bo Song Chen

Hailong Liu

Jie Hou

Xiang Zhang

Li Hui Lu

Shuai Yue

Bo Chen

Xiaolong Zhang

Jian Hua Liu

Xiao Liu

Feng Rao

Bin Xiao

Li Lu

Bin Zhang

Haibo Liu

Pinlin Chen

Deyuan Li

Eryu Wang

Keren Li

Lou Li

Duling Lu

Lu Li

Jian Liu

A method of presenting interactive content at a client device is disclosed. The client device records, in real-time, an audio stream of a piece of multimedia content broadcast by a content display device and sends an audio fingerprint of the piece of the multimedia content to a server. The server then determines, based on the audio fingerprint, an identifier of the piece of multimedia content, retrieves, based on the identifier of the piece of multimedia content, interactive content associated with the piece of multimedia content, and returns the interactive content associated with the piece of multimedia content to the client device. After receiving, from the server, the interactive content associated with the piece of multimedia content, the client device renders the interactive content to the user of the client device.

Method and system for interacting with audience of multimedia content

A method of interacting with an audience of multimedia content is disclosed. The method includes receiving, from a client device, data associated with a piece of multimedia content from a group of pieces of multimedia content that is presented to a user of the client device. The data is obtained at the client device in response to an instruction provided to the client device by the user. The method includes determining, based on the data, an identifier of the piece of multimedia content from a set of identifiers, each of which identifies a piece of multimedia content from the group of pieces of multimedia content. The method includes retrieving, based on the identifier of the piece of multimedia content, interactive content associated with the piece of multimedia content. The method includes sending the interactive content to the client device such that the client device presents the interactive content to the user.

A method of recognizing speech commands includes generating a background acoustic model for a sound using a first sound sample, the background acoustic model characterized by a first precision metric. A foreground acoustic model is generated for the sound using a second sound sample, the foreground acoustic model characterized by a second precision metric. A third sound sample is received and decoded by assigning a weight to the third sound sample corresponding to a probability that the sound sample originated in a foreground using the foreground acoustic model and the background acoustic model. The method further includes determining if the weight meets predefined criteria for assigning the third sound sample to the foreground and, when the weight meets the predefined criteria, interpreting the third sound sample as a portion of a speech command. Otherwise, recognition of the third sound sample as a portion of a speech command is forgone.

Method and system for recognizing speech commands using background and foreground acoustic models

An automatic speech recognition method includes at a computer having one or more processors and memory for storing one or more programs to be executed by the processors, obtaining a plurality of speech corpus categories through classifying and calculating raw speech corpus; obtaining a plurality of classified language models that respectively correspond to the plurality of speech corpus categories through a language model training applied on each speech corpus category; obtaining an interpolation language model through implementing a weighted interpolation on each classified language model and merging the interpolated plurality of classified language models; constructing a decoding resource in accordance with an acoustic model and the interpolation language model; and decoding input speech using the decoding resource, and outputting a character string with a highest probability as a recognition result of the input speech.

Method and system for building a topic specific language model for use in automatic speech recognition

A computer system obtains a streaming media signal source, selects a testing sample from the streaming media signal source, records characteristics of the testing sample, and obtains an expected output according to the characteristics of the testing sample. Next, the computer system converts the testing sample into a digital streaming format preset by a service provider and initiates a media recognition request according to the testing sample in the digital streaming format to the service provider. After receiving a media recognition result of the testing sample returned by the service provider according to the media recognition request, the computer system compares the media recognition result with the expected output and indicates whether the service provider is normal in accordance with the comparison result.

Method and system for testing and monitoring a real-time streaming media recognition service provider

A method of recognizing speech is provided that includes generating a decoding network that includes a primary sub-network and a classification sub-network. The primary sub-network includes a classification node corresponding to the classification sub-network. The classification sub-network corresponds to a group of uncommon words. A speech input is received and decoded by instantiating a token in the primary sub-network and passing the token through the primary network. When the token reaches the classification node, the method includes transferring the token to the classification sub-network and passing the token through the classification sub-network. When the token reaches an accept node of the classification sub-network, the method includes returning a result of the token passing through the classification sub-network to the primary sub-network. The result includes one or more words in the group of uncommon words. A string corresponding to the speech input is output that includes the one or more words.

Method and system for automatic speech recognition

A method and device for performing audio recognition, including: collecting a first audio document to be recognized; initiating calculation of first characteristic information of the first audio document, including: conducting time-frequency analysis for the first audio document to generate a first preset number of phase channels; and extracting at least one peak value characteristic point from each phase channel of the first preset number of phrase channels, where the at least one peak value characteristic point of each phase channel constitutes the peak value characteristic point sequence of said each phase channel; and obtaining a recognition result for the first audio document, wherein the recognition result is identified based on the first characteristic information, and wherein the first characteristic information is calculated based on the respective peak value characteristic point sequences of the preset number of phase channels.

Method and device for audio recognition

An electronic device with one or more processors, memory, and a display detects a first trigger event and, in response to detecting the first trigger event, collects a audio sample of environmental audio data associated with a media item. The device transmits information corresponding to the audio sample to a server. In response to transmitting the information, the device obtains attribute information corresponding to the audio sample, where the attribute information includes metadata for the media item, a time indicator of a position of the audio sample in the media item, and stream information for the media item. The device displays a portion of the attribute information. The device detects a second trigger event and, in response to detecting the second trigger event: determines a last obtained time indicator; streams the media item based on the stream information; and presents the media item from the last obtained time indicator.

Method and system for performing an audio information collection and query

Systems and methods are provided for program identification. For example, a first audio fingerprint corresponding to a first audio signal is acquired; whether one or more second audio fingerprints in a predetermined fingerprint database match with the first audio fingerprint is detected, a second audio fingerprint corresponding to a second audio signal; and in response to one of the second audio fingerprints matching with the first audio fingerprint, a program associated with the matching second audio signal is provided as a result for program identification associated with the first audio signal.

Systems and methods for program identification

A method of providing an interactive content to a prospective user at a mobile device, the mobile device including a non-transitory computer readable medium including a computer executable program code and a processor for executing the computer executable program code is described. The method includes steps for initiating capture of an audio stream by shaking the mobile device; capturing the audio stream via a microphone in the mobile device; converting the captured audio stream into an audio fingerprint; sending the audio fingerprint to a server; receiving the interactive content from the server if there is a match between audio fingerprints stored on the server, and the audio fingerprint sent by the mobile device; and displaying the interactive content on the mobile device.

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Shenzhen, China

Dadong Xie