SOUNDHOUND AI IP, LLC

A neural TTS system is trained to generate key acoustic frames at variable rates while omitting other frames. The frame skipping depends on the acoustic features to be generated for the input text. The TTS system can interpolate frames between the key frames at a target rate for a vocoder to synthesis audio samples.

Systems and methods for searching databases by sound data input are provided herein. A service provider may have a need to make their database(s) searchable through search technology. However, the service provider may not have the resources to implement such search technology. The search technology may allow for search queries using sound data input. The technology described herein provides a solution addressing the service provider's need, by giving a search technology that furnishes search results in a fast, accurate manner. In further embodiments, systems and methods to monetize those search results are also described herein.

Various approaches relate to user defined content filtering in media playing devices of undesirable content represented in stored and real-time content from content providers. For example, video, image, and/or audio data can be analyzed to identify and classify content included in the data using various classification models and object and text recognition approaches. Thereafter, the identification and classification can be used to control presentation and/or access to the content and/or portions of the content. For example, based on the classification, portions of the content can be modified (e.g., replaced, removed, degraded, etc.) using one or more techniques (e.g., media replacement, media removal, media degradation, etc.) and then presented.

[Object] Technology is provided to enable a mobile terminal to function as a digital assistant even when the mobile terminal is in a state where it cannot communicate with a server apparatus. [Solution] When a user terminal 200 receives a query A from a user, user terminal 200 sends query A to a server 100 . Server 100 interprets the meaning of query A using a grammar A. Server 100 obtains a response to query A based on the meaning of query A and sends the response to user terminal 200 . Server 100 further sends grammar A to user terminal 200 . That is, server 100 sends to user terminal 200 a grammar used to interpret the query received from user terminal 200.

A computer-implemented method is provided to support a food ordering system for food items from a menu of a restaurant using natural language. Expressions made for ordering are used to recommend a food item that a user has a high probability of wanting to include in an order. The recommendation engine is trained using machine learning. Expressions are collected and parsed to identify words that might indicate food items offered by the restaurant. The words are provided to a restaurant owner to identify food items on a menu, with which the words are associated.

The application provides an apparatus, platform, method and medium for intention importance interference. The apparatus includes an interface configured to receive user-related information; and a processor coupled to the interface and configured to: extract data related to different aspects of a user from the user-related information; generate a plurality of intention probes based on the data related to different aspects of the user, each intention probe comprising an intention and associated data items; infer an importance of each intention probe by calculating a score of each associated data items of the intention probe based on the data related to different aspects of the user; and provide information associated with an intention probe with a highest importance.

Systems and methods improve automatic speech recognition using voice morphing and voiceprint-based personalization. Speech audio from diverse speakers may be transformed to one or more target voices to enable accurate phoneme inference by an acoustic model trained for the target voice, with the models trained separately or jointly. Speech recognition requests may include a voiceprint that biases recognition toward the speaker's voice, and speech audio may be used to update the voiceprint, which is returned for use in subsequent speech recognition requests.

Custom acoustic models can be configured by developers by providing audio files with custom recordings. The custom acoustic model is trained by tuning a baseline model using the audio files. Audio files may contain custom noise to apply to clean speech for training. The custom acoustic model is provided as an alternative to a standard acoustic model. A speech recognition system can select an acoustic model for use upon receiving metadata about the device conditions or type. Speech recognition is performed on speech audio using one or more acoustic models. The result can be provided to developers through the user interface, and an error rate can be computed and also provided.

As audio (1) is input to an extension of a browser, the extension transmits the audio (1) to a language processing server. A speech recognition unit obtains a text (1) corresponding to the audio (1), and transmits the text (1) to a natural language understanding unit. In the natural language understanding unit, an information processing unit identifies a URL (1) corresponding to the text (1), and transmits the URL (1) to the browser. The extension passes the URL (1) to a browsing function. The browsing function uses the URL (1) to access a web server. The web server transmits a web page (1) corresponding to the URL (1) to the browser. The browsing function shows a screen corresponding to the web page (1) on a display.

A driver interface for use within an automobile provides responses to voice commands issued for example by a driver of the automobile. The interface includes a camera and microphone for capturing image data such as gestures and audio data from the automobile driver. The image data and audio data are processed to extract image and linguistic features from the image and audio data, which image and linguistic features are processed to interpret and infer a meaning of the voice command.