Abstract: The present disclosure provides an earphone comprising a sound production component and an ear hook. In a wearing state, the ear hook is configured to place the sound production component at a position near an ear canal but not blocking the ear canal. An inner contour of the ear hook's projection on a user's sagittal plane includes a first curve having an extremum point in a first direction. The first direction is perpendicular to a long-axis direction of a projection of the sound production component on the sagittal plane. The extremum point is located behind a projection point of an upper vertex of the ear hook on the sagittal plane, and the upper vertex is a highest point of an inner contour of the ear hook along the user's vertical axis. An inclination angle of the long-axis direction relative to a horizontal direction is within a range of 13°-21°.

Abstract: The present disclosure provides an earphone comprising a sound production component and an ear hook. In a wearing state, the ear hook is configured to place the sound production component at a position near an ear canal but not blocking the ear canal. An inner contour of the ear hook's projection on a user's sagittal plane includes a first curve having an extremum point in a first direction. The first direction is perpendicular to a long-axis direction of a projection of the sound production component on the sagittal plane. The extremum point is located behind a projection point of an upper vertex of the ear hook on the sagittal plane, and the upper vertex is a highest point of an inner contour of the ear hook along the user's vertical axis. An inclination angle of the long-axis direction relative to a horizontal direction is within a range of 13°-21°.

Abstract: A human-machine interaction method and apparatus based on artificial intelligence. In the method, a user-entered interaction sentence is received, and whether to generate an interaction result corresponding to the interaction sentence is determined; and interaction information to be presented to the user is determined based on a determining result, the interaction information including at least one of following items: the generated interaction result corresponding to the interaction sentence, or a search result corresponding to the interaction sentence in a search engine.

Abstract: Embodiments of the present disclosure disclose an artificial intelligence based method and apparatus for classifying a voice-recognized text. A specific embodiment of the method includes: acquiring a current interactive text of a voice query from a user; analyzing the current interactive text using a lexical analyzer to obtain a current lexical structure; determining whether the current lexical structure matches a template of a category in a classifier; and classifying, if the current lexical structure matches the template of the category in the classifier, the current interactive text corresponding to the current lexical structure into the category belonging to the matched template. The embodiment can fast classify texts, effectively reduce the magnitude of manually annotated texts, and improve the annotation efficiency in intelligent voice interaction services.

Abstract: The disclosure discloses a human-machine interaction method and apparatus based on artificial intelligence. A specific embodiment of the method comprises: receiving a user-entered interaction sentence, and determining whether to generate an interaction result corresponding to the interaction sentence; and determining interaction information to be presented to the user based on a determining result, the interaction information comprising at least one of following items: the generated interaction result corresponding to the interaction sentence, or a search result corresponding to the interaction sentence in a search engine.

Abstract: Embodiments of the present disclosure disclose an artificial intelligence based method and apparatus for classifying a voice-recognized text. A specific embodiment of the method includes: acquiring a current interactive text of a voice query from a user; analyzing the current interactive text using a lexical analyzer to obtain a current lexical structure; determining whether the current lexical structure matches a template of a category in a classifier; and classifying, if the current lexical structure matches the template of the category in the classifier, the current interactive text corresponding to the current lexical structure into the category belonging to the matched template. The embodiment can fast classify texts, effectively reduce the magnitude of manually annotated texts, and improve the annotation efficiency in intelligent voice interaction services.