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US 11,900,959 B2Granted
Speech emotion recognition method and apparatus
AssigneeHuawei Technologies Co., Ltd.
InventorsYang Zhang, Oxana Verkholyak, Alexey Karpov, Li Qian
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Abstract
A plurality of pieces of emotional state information corresponding to a plurality of speech frames in a current utterance are obtained based on a first neural network model; statistical operation is performed on the plurality of pieces of emotional state information, to obtain a statistical result, and then the emotional state information corresponding to the current utterance is obtained based on a second neural network device, the statistical result corresponding to the current utterance, and statistical results corresponding to a plurality of utterances before the current utterance.
Claims23
A method, comprising:
- determining, based on a first neural network model, a plurality of pieces of emotional state information corresponding to a plurality of speech frames comprised in a current utterance in a target dialog, wherein the plurality of speech frames have a one-to-one correspondence with the plurality of pieces of emotional state information, and each piece of emotional state information represents an emotional state corresponding to a corresponding speech frame;
- performing a statistical operation on the plurality of pieces of emotional state information to obtain a statistical result, wherein the statistical result corresponds to the current utterance;
- and
- determining emotional state information corresponding to the current utterance, the determining being based on a second neural network model, the statistical result corresponding to the current utterance, and n-1 statistical results corresponding to n-1 utterances before the current utterance;
- and
- wherein the n-1 utterances have a one-to-one correspondence with the n-1 statistical results, a statistical result corresponding to each utterance in the n-1 utterances is obtained by performing a statistical operation on a plurality of pieces of emotional state information corresponding to a plurality of speech frames comprised in the respective utterance, the n-1 utterances belong to the target dialog, and n is an integer greater than 1.
3 more elements
An apparatus, comprising:
- a non-transitory memory, configured to store programs;
- and
- a processor, configured to execute the programs stored in the memory, wherein when at least one program stored in the memory is executed, the processor is configured to:
- determine, based on a first neural network model, a plurality of pieces of emotional state information corresponding to a plurality of speech frames comprised in a current utterance in a target dialog, wherein the plurality of speech frames have a one-to-one correspondence with the plurality of pieces of emotional state information, and each piece of emotional state information represents an emotional state corresponding to the corresponding speech frame;
- perform a statistical operation on the plurality of pieces of emotional state information to obtain a statistical result, wherein the statistical result corresponds to the current utterance;
- and
- determine emotional state information corresponding to the current utterance, the determining being based on a second neural network model, the statistical result corresponding to the current utterance, and n-1 statistical results corresponding to n-1 utterances before the current utterance;
- and
- wherein the n-1 utterances have a one-to-one correspondence with the n-1 statistical results, a statistical result corresponding to each utterance in the n-1 utterances is obtained by performing statistical operation on a plurality of pieces of emotional state information corresponding to a plurality of speech frames comprised in the respective utterance, the n-1 utterances belong to the target dialog, and n is an integer greater than 1.
6 more elements
A non-transitory computer readable storage medium storing executable instructions, the executable instructions including instructions for:
- determining, based on a first neural network model, a plurality of pieces of emotional state information corresponding to a plurality of speech frames comprised in a current utterance in a target dialog, wherein the plurality of speech frames have a one-to-one correspondence with the plurality of pieces of emotional state information, and each piece of emotional state information represents an emotional state corresponding to a corresponding speech frame;
- performing a statistical operation on the plurality of pieces of emotional state information to obtain a statistical result, wherein the statistical result corresponds to the current utterance;
- and
- determining emotional state information corresponding to the current utterance, the determining being based on a second neural network model, the statistical result corresponding to the current utterance, and n-1 statistical results corresponding to n-1 utterances before the current utterance;
- and
- wherein the n-1 utterances have a one-to-one correspondence with the n-1 statistical results, a statistical result corresponding to each utterance in the n-1 utterances is obtained by performing a statistical operation on a plurality of pieces of emotional state information corresponding to a plurality of speech frames comprised in the respective utterance, the n-1 utterances belong to the target dialog, and n is an integer greater than 1.
3 more elements
Dependencies are inferred from the claim text.