Abstract: Mechanisms are provided to implement an efficient translating mechanism to efficiently translating social media posts. A source language to be used to translate the social media post is identified based on words within the social media post. A highest classification is identified and the social media post is translated from the source language to a target language using a translation level associated with the highest classification. In the translation, each word and its related meaning in the target language are identified from a multi-language data structure; each word is categorized into its associated part of speech; a sentence is generated in the target language; and natural language processing is performed on each sentence in the target language to identity the existence of ambiguous connotations. Responsive to each sentence failing have any ambiguous connotations, a social medial post is generated in the target language utilizing the generated sentences.

Abstract: Described are techniques for linking generating a skill-stored user profile, and linking same with a natural language processing (NLP) system-stored user profile. In at least some examples, a user may provide a natural language input to a NLP system. The NLP system may determine a skill is to process to perform an action responsive to the natural language input. To perform the action, the skill may require the user have a user profile stored by the skill, but the user may not have such a user profile. However, the NLP system may store a user profile for the user. The NLP system may determine the user profile stored thereby and may send, with user permission, information in the user profile to the skill. The skill may use the received information to generate and store a user profile for the user. Thereafter, the skill may provide the NLP system with a user profile identifier that the skill may use to identify the user's profile stored thereby.

Abstract: A speech recognition system includes an encoder to convert an input acoustic signal into a sequence of encoder states, an alignment decoder to identify locations of encoder states in the sequence of encoder states that encode transcription outputs, a partition module to partition the sequence of encoder states into a set of partitions based on the locations of the identified encoder states, and an attention-based decoder to determine the transcription outputs for each partition of encoder states submitted to the attention-based decoder as an input. Upon receiving the acoustic signal, the system uses the encoder to produce the sequence of encoder states, partitions the sequence of encoder states into the set of partitions based on the locations of the encoder states identified by the alignment decoder, and submits the set of partitions sequentially into the attention-based decoder to produce a transcription output for each of the submitted partitions.

Abstract: Described herein are methods, systems and computer program products for determining a decodability index for one or more words. One of the methods of determining a decodability index for one or more words comprises receiving one or more words for analysis; analyzing the received one or more words using a plurality of effects; and assigning a decodability index to the received one or more words based on the analysis of the received one or more words using the plurality of effects, wherein the assigned decodability index indicates an ability of a person to pronounce or sound out the one or more words.

Abstract: A method and an apparatus for generating information are provide according to embodiments of the disclosure. A specific embodiment of the method comprises: acquiring to-be-analyzed information according to a target keyword; and inputting the to-be-analyzed information into a pre-established sentiment analysis model to generate sentiment orientation information of the to-be-analyzed information. The sentiment analysis model is obtained through following training: acquiring untagged sample data and tagged sample data; generating tag information corresponding to the untagged sample data using a pre-established tag generation model, and using the untagged sample data and the generated tag information as extended sample data, the tag generation model being used to represent a corresponding relationship between the untagged sample data and the tag information; and obtaining the sentiment analysis model by training using the tagged sample data and the extended sample data.

Abstract: Methods and systems for a transportation vehicle are provided. One method includes receiving a user input for a valid communication session by a processor executable, digital assistant at a device on a transportation vehicle; tagging by the digital assistant, the user input words with a grammatical connotation; generating an action context, a filter context and a response context by a neural network, based on the tagged user input; storing by the digital assistant, a key-value pair for a parameter of the filter context at a short term memory, based on an output from the neural network; updating by the digital assistant, the key-value pair at the short term memory after receiving a reply to a follow-up request and another output from the trained neural network; and providing a response to the reply by the digital assistant.

Abstract: A speech recognition method includes obtaining captured voice information, and determining semantic information of the captured voice information; segmenting the captured voice information to obtain voice segments when the semantic information does not satisfy a preset rule, and extracting voiceprint information of the voice segments; obtaining an unmatched voiceprint information from a local voiceprint database; matching the voiceprint information of the voice segments with the unmatched voiceprint information to determine a set of filtered voice segments having voiceprint information that successfully matches the unmatched voiceprint information; combining the set of filtered voice segments to obtain combined voice information, and determining combined semantic information of the combined voice information; and using the combined semantic information as a speech recognition result when the combined semantic information satisfies the preset rule.

Abstract: Provided are a computer program product, system, and method for generating a plurality of document plans to generate questions from source text. The declarative source text is processed to generate a plurality of document plan data structures. To generate each document plan data structure, at least a portion of the declarative source text is included in the document plan data structure. A determination is made of at least one relation of arguments in the declarative source text. The determined at least one relation and the arguments are indicated in the document plan data structure. Entity types of the arguments are determined and indicated in the document plan data structure. A natural language generation module processes each of the document plan data structures to generate a plurality of questions, which are stored with the declarative source text.

Abstract: In some examples, a system may receive from a device, speech sound patterns corresponding to a voice input related to equipment. Further, the system may determine an identity of a person associated with the device, and may identify the equipment related to the voice input. Using at least one of the received speech sound patterns or a text conversion of the speech sound patterns, along with an equipment history of the identified equipment, as input to one or more machine learning models, the system may determine, at least partially, an instruction related to the equipment. Additionally, the system may send, to the device, the instruction related to the equipment as an audio file for playback on the device.

Abstract: The present disclosure is generally directed to the generation of voice-activated data flows in interconnected network. The voice-activated data flows can include input audio signals that include a request and are detected at a client device. The client device can transmit the input audio signal to a data processing system, where the input audio signal can be parsed and passed to the data processing system of a service provider to fulfill the request in the input audio signal. The present solution is configured to conserve network resources by reducing the number of network transmissions needed to fulfill a request.

Abstract: A method for using speech disfluencies detected in speech input to assist in interpreting the input is provided. The method includes providing access to a set of content items with metadata describing the content items, and receiving a speech input intended to identify a desired content item. The method further includes detecting a speech disfluency in the speech input and determining a measure of confidence of a user in a portion of the speech input following the speech disfluency. If the confidence measure is lower than a threshold value, the method includes determining an alternative query input based on replacing the portion of the speech input following the speech disfluency with another word or phrase. The method further includes selecting content items based on comparing the speech input, the alternative query input (when the confidence measure is low), and the metadata associated with the content items.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for speech endpointing based on word comparisons are described. In one aspect, a method includes the actions of obtaining a transcription of an utterance. The actions further include determining, as a first value, a quantity of text samples in a collection of text samples that (i) include terms that match the transcription, and (ii) do not include any additional terms. The actions further include determining, as a second value, a quantity of text samples in the collection of text samples that (i) include terms that match the transcription, and (ii) include one or more additional terms. The actions further include classifying the utterance as a likely incomplete utterance or not a likely incomplete utterance based at least on comparing the first value and the second value.

Abstract: An apparatus comprising one or more processors, a communication circuit, and a memory for storing instructions, which when executed, performs a method of recognizing a user utterance. The method comprises: receiving first data associated with a user utterance, performing, a first determination to determine whether the user utterance includes the first data and a specified word, performing a second determination to determine whether the first data includes the specified word, transmitting the first data to an external server, receiving a text generated from the first data by the external server, performing a third determination to determine whether the received text matches the specified word, and determining whether to activate the voice-based input system based on the third determination.

Abstract: A system for creating a synthetic voice identifier may include a plurality of synthesized voice authorization (SVA) devices and a biometric combinatory device (BCD). The SVAs may be communicatively coupled to the BCD via a network and may communicate utilizing a markup language. The SVA devices may capture an audio signal of a voice of a user, modify the audio signal with a randomized audio frequency signal to generate a modified audio signal, and communicate, the modified audio signal as a synthesized voice signal associated with the user.

Abstract: Many processes for audio signal processing can benefit from voice activity detection, which aims to detect the presence of speech as opposed to silence or noise. The present disclosure describes, among other things, leveraging energy-based features of voice and insights on first and second formant frequencies of vowels to provide a low-complexity and low-power voice activity detector. A pair of two channels is provided whereby each channel is configured to detect voice activity in respective frequency bands of interest. Simultaneous activity detected in both channels can be a sufficient condition for determining that voice is present. More channels or pairs of channels can be used to detect different types of voices to improve detection and/or to detect voices present in different audio streams.

Abstract: A method of performing speech recognition, comprises, at a first device: receiving an audio signal representing speech; performing a first data integrity check operation on the received audio signal; performing a speaker recognition process on the received audio signal; forwarding the received audio signal to a second device, wherein the second device comprises a speech recognition function; and forwarding an output of the first data integrity check operation to the second device.

Abstract: Embodiments of the present disclosure provide methods, systems, apparatuses, and computer program products for generating a searchable transcript of a group-based audio/video connection within a group-based communication system.

Abstract: A speech signal processing method is performed at a terminal device, including: obtaining a recorded signal and a to-be-output speech signal, the recorded signal including a noise signal and an echo signal; calculating a loop transfer function according to the recorded signal and the speech signal; calculating a power spectrum of the echo signal and a power spectrum of the noise signal according to the recorded signal, the speech signal, and the loop transfer function; calculating a frequency weighted coefficient according to the two power spectra of the echo signal and the noise signal; adjusting a frequency amplitude of the speech signal based on the frequency weighted coefficient; and outputting the adjusted speech signal to a speaker electrically coupled to the terminal device. As such, the frequency amplitude of the speech signal is automatically adjusted according to the relative frequency distribution of a noise signal and the speech signal.

Abstract: A circuit for sound activity detection includes a transducer (106) adapted to generate an electrical signal based on detected sound; a variable gain amplifier adapted to amplify the electrical signal to generate an amplified electrical signal; a comparator adapted to compare the amplified electrical signal with at least one first threshold level to generate a comparison signal indicating comparator events; and a control circuit adapted to generate, based on the comparison signal, a gain control signal for controlling the gain of the variable gain amplifier, and a sound activity alert signal indicating the detection of sound activity.

Abstract: A command-processing server provides natural language services to applications. More specifically, the command-processing server receives natural language inputs from users for use in applications such as virtual assistants. Some user inputs create user-defined rules that consist of trigger conditions and of corresponding actions that are executed when the triggers fire. The command-processing server stores the rules received from a user in association with the specific user. The command-processing server also identifies rules that can be generalized across users and promoted into generic rules applicable to many or all users. The generic rules may or may not have an associated context constraining their application.