Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting, from among a collection of videos, a set of candidate videos that (i) are identified as being associated with a particular song, and (ii) are classified as a cappella video recordings; extracting, from each of the candidate videos of the set, a monophonic melody line from an audio channel of the candidate video; selecting, from among the set of candidate videos, a subset of the candidate videos based on a similarity of the monophonic melody line of the candidate videos of the subset with each other; and providing, to a recognizer that recognizes songs from sounds produced by a human voice, (i) an identifier of the particular song, and (ii) one or more of the monophonic melody lines of the candidate videos of the subset.

Abstract: An input signal that includes linguistic content in a first language may be received by a computing device. The linguistic content may include text or speech. The computing device may associate the linguistic content in the first language with one or more phonemes from a second language. The computing device may also determine a phonemic representation of the linguistic content in the first language based on use of the one or more phonemes from the second language. The phonemic representation may be indicative of a pronunciation of the linguistic content in the first language according to speech sounds of the second language.

Abstract: An input signal that includes linguistic content in a first language may be received by a computing device. The linguistic content may include text or speech. Based on an acoustic feature comparison between a plurality of first-language speech sounds and a plurality of second-language speech sounds, the computing device may associate the linguistic content in the first language with one or more phonemes from a second language. The computing device may also determine a phonemic representation of the linguistic content in the first language based on use of the one or more phonemes from the second language. The phonemic representation may be indicative of a pronunciation of the linguistic content in the first language according to speech sounds of the second language.

Abstract: A device may receive a plurality of speech sounds that are indicative of pronunciations of a first linguistic term. The device may determine concatenation features of the plurality of speech sounds. The concatenation features may be indicative of an acoustic transition between a first speech sound and a second speech sound when the first speech sound and the second speech sound are concatenated. The first speech sound may be included in the plurality of speech sounds and the second speech sound may be indicative of a pronunciation of a second linguistic term. The device may cluster the plurality of speech sounds into one or more clusters based on the concatenation features. The device may provide a representative speech sound of the given cluster as the first speech sound when the first speech sound and the second speech sound are concatenated.

Abstract: A first-pitch metric function based on a first audio sample and a second pitch-metric function based on a second audio sample may be determined. The first and second pitch-metric functions may have either local minima or local maxima that correspond to candidate pitch values of the first and the second audio samples, respectively. The first and the second pitch-metric functions may be transformed to generate a first and a second transformed pitch-metric function, respectively. A correlation function based on a correlation between the first and the second transformed pitch-metric function may also be determined. A lower-dimensionality representation of the correlation function may further be determined. The lower-dimensionality representation may convey information indicative of pitch dynamics between the first and second audio sample. A computing device having a processor and a memory may perform an action based on the information indicative of the pitch dynamics.

Abstract: Methods and systems for adaptation of synthetic speech in an environment are described. In an example, a device, which may include a text-to-speech (TTS) module, may be configured to determine characteristics of an environment of the device. The device also may be configured to determine, based on the one or more characteristics of the environment, speech parameters that characterize a voice output of the text-to-speech module. Further, the device may be configured to process a text to obtain the voice output corresponding to the text based on the speech parameters to account for the one or more characteristics of the environment.