Abstract:
A method comprising: receiving a request to create a virtual communication channel between the real world and a virtual reality environment, the virtual reality environment comprising both audio and visual content; in response to receiving the request, causing a virtual window to be displayed in the virtual reality environment; and causing distorted audio from real world surroundings of a user making the request to emanate from the virtual window.
Abstract:
A system that incorporates the subject disclosure may include, for example, receive user speech captured at a second end user device during a communication session between the second end user device and a first end user device, apply speech recognition to the user speech, identify an unclear word in the user speech based on the speech recognition, adjust the user speech to generate adjusted user speech by replacing all or a portion of the unclear word with replacement audio content, and provide the adjusted user speech to the first end user device during the communication session. Other embodiments are disclosed.
Abstract:
In one embodiment, an audio decoder for decoding an encoded audio bitstream is disclosed. The audio decoder is capable of being operated in at least three different decoding modes. The audio decoder includes a demultiplexer for obtaining audio data and control information from the encoded audio bitstream. The audio decoder also includes a first audio decoder configured to operate in a first decoding mode using a first decoding technique and a second audio decoder configured to operate in a second decoding mode using a second decoding technique. The audio decoder also includes a pitch predictor integrated into the second audio decoder. The pitch predictor includes a long-term prediction filter and a short-term prediction filter. The audio decoder further includes a selector for selecting one of the at least three different decoding modes based on at least some of the control information.
Abstract:
A method by an electronic device for compensating for environmental noise in text-to-speech (TTS) speech output includes: measuring environmental noise using a microphone signal; determining sound characteristics of the measured environmental noise; dynamically predicting expected future sound characteristics of the environmental noise based on the determined sound characteristics of the measured environmental noise; receiving a text input at a TTS engine at the device, with the TTS engine configured to convert the text input into a speech output signal; determining text characteristics of the text input at the TTS engine; and at the TTS engine, dynamically adapting the speech output signal based on the determined text characteristics of the text input and the predicted expected future sound characteristics of the environmental noise.
Abstract:
A visualization system with audio capability includes one or more display devices, one or more microphones, one or more speakers, and audio processing circuitry. While a display device displays a holographic image to a user, a microphone inputs an utterance of the user, or a sound from the user's environment, and provides it to the audio processing circuitry. The audio processing circuitry processes the utterance (or other sound) in real-time to add an audio effect associated with the image to increase realism, and outputs the processed utterance (or other sound) to the user via the speaker in real-time, with very low latency.
Abstract:
In one embodiment, an audio decoder for decoding an audio bitstream is disclosed. The decoder includes a first decoding module adapted to operate in a first coding mode and a second decoding module adapted to operate in a second coding mode, the second coding mode being different from the first coding mode. The decoder further includes a pitch filter in either the first coding mode or the second coding mode, the pitch filter adapted to filter a preliminary audio signal generated by the first decoding module or the second decoding module to obtain a filtered signal. The pitch filter is selectively enabled or disabled based on a value of a first parameter encoded in the audio bitstream, the first parameter being distinct from a second parameter encoded in the audio bitstream, the second parameter specifying a current coding mode of the audio decoder.
Abstract:
Systems and methods for improving communication over a network are provided. A system for improving communication over a network, comprises a detection module capable of detecting data indicating a problem with a communication between at least two participants communicating via communication devices over the network, a management module capable of analyzing the data to determine whether a participant is dissatisfied with the communication, wherein the management module includes a determining module capable of determining that the participant is dissatisfied, and identifying an event causing the dissatisfaction, and a resolution module capable of providing a solution for eliminating the problem.
Abstract:
A voice quality conversion system includes: an analysis unit which analyzes sounds of plural vowels of different types to generate first vocal tract shape information for each type of the vowels; a combination unit which combines, for each type of the vowels, the first vocal tract shape information on that type of vowel and the first vocal tract shape information on a different type of vowel to generate second vocal tract shape information on that type of vowel; and a synthesis unit which (i) combines vocal tract shape information on a vowel included in input speech and the second vocal tract shape information on the same type of vowel to convert vocal tract shape information on the input speech, and (ii) generates a synthetic sound using the converted vocal tract shape information and voicing source information on the input speech to convert the voice quality of the input speech.
Abstract:
A method and system is disclosed for non-parametric speech conversion. A text-to-speech (TTS) synthesis system may include hidden Markov model (HMM) HMM based speech modeling for both synthesizing output speech. A converted HMM may be initially set to a source HMM trained with a voice of a source speaker. A parametric representation of speech may be extract from speech of a target speaker to generate a set of target-speaker vectors. A matching procedure, carried out under a transform that compensates for speaker differences, may be used to match each HMM state of the source HMM to a target-speaker vector. The HMM states of the converted HMM may be replaced with the matched target-speaker vectors. Transforms may be applied to further adapt the converted HMM to the voice of target speaker. The converted HMM may be used to synthesize speech with voice characteristics of the target speaker.
Abstract:
Systems and methods for adaptively processing speech to improve voice intelligibility are described. These systems and methods can adaptively identify and track formant locations, thereby enabling formants to be emphasized as they change. As a result, these systems and methods can improve near-end intelligibility, even in noisy environments. The systems and methods can be implemented in Voice-over IP (VoIP) applications, telephone and/or video conference applications (including on cellular phones, smart phones, and the like), laptop and tablet communications, and the like. The systems and methods can also enhance non-voiced speech, which can include speech generated without the vocal track, such as transient speech.