Abstract: A pre-training method executed by a training apparatus includes converting an input acoustic feature amount sequence into a corresponding intermediate acoustic feature amount sequence having a first length using a first conversion model to which a conversion model parameter is provided, converting a correct answer symbol sequence to generate a first frame unit symbol sequence having the first length and generating a second frame unit symbol sequence having the first length by delaying the first frame unit symbol sequence by one frame, converting the second frame unit symbol sequence into an intermediate character feature amount sequence having the first length using a second conversion model to which a character feature amount estimation model parameter is provided, and performing label estimation using an estimation model to which an estimation model parameter is provided based on the intermediate acoustic feature amount sequence and the intermediate character feature amount sequence.

Abstract: A learning device includes a learning unit learning, with a first feature value having a first feature and given a first value label, a second feature value having a second feature and given a second value label and a third feature value having a feature between the first feature and the second feature and given a value label having a value between the first value label and the second value label as teacher data, a model for estimating which of the first feature and the second feature an input feature value sequence has.

Abstract: An identification model learning device capable of improving an identification model for a particular speech vocal sound is provided. An identification model learning device includes: an identification model learning unit configured to learn, based on learning data including a feature sequence in a frame unit of a speech and a binary label indicating whether the speech is a particular speech, an identification model including an input layer that accepts the feature sequence in the frame unit as an input and outputs an output result to an intermediate layer, one or more intermediate layers that accept an output result of the input layer or an immediately previous intermediate layer as an input and output a processing result, an integration layer that accepts an output result of a final intermediate layer as an input and outputs a processing result in a speech unit, and an output layer that outputs the label from the output of the integration layer.