0000000000726366

AUTHOR

Mark A. Clements

showing 3 related works from this author

Decoding Children's Social Behavior

2013

We introduce a new problem domain for activity recognition: the analysis of children's social and communicative behaviors based on video and audio data. We specifically target interactions between children aged 1-2 years and an adult. Such interactions arise naturally in the diagnosis and treatment of developmental disorders such as autism. We introduce a new publicly-available dataset containing over 160 sessions of a 3-5 minute child-adult interaction. In each session, the adult examiner followed a semi-structured play interaction protocol which was designed to elicit a broad range of social behaviors. We identify the key technical challenges in analyzing these behaviors, and describe met…

Behavior Psychology Dataset Video analysis Speech Analysis AutismInter-action protocolsSocial and communicative behaviorInteraction protocol02 engineering and technologycomputer.software_genreAnnan data- och informationsvetenskapSession (web analytics)Activity recognitionTechnical challenges0202 electrical engineering electronic engineering information engineeringmedicineSocial behaviorAudio signal processingMultimediabusiness.industryDevelopmental disorders020207 software engineeringmedicine.diseaseSemi-structuredResearch questionsActivity recognitionProblem domainKey (cryptography)Autism020201 artificial intelligence & image processingArtificial intelligencePsychologybusinessOther Computer and Information SciencecomputerCognitive psychologySocial behavior2013 IEEE Conference on Computer Vision and Pattern Recognition
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A Study of Perceptron Mapping Capability to Design Speech Event Detectors

2006

Event detection is a fundamental yet critical component in automatic speech recognition (ASR) systems that attempt to extract knowledge-based features at the front-end level. In this context, it is common practice to design the detectors inside well-known frameworks based on artificial neural network (ANN) or support vector machine (SVM). In the case of ANN, speech scientists often design their detector architecture relying on conventional feed-forward multi-layer perceptron (MLP) with sigmoidal activation function. The aim of this paper is to introduce other ANN architectures inside the context of detection-based ASR. In particular, a bank of feed-forward MLPs using sinusoidal activation f…

Artificial neural networkComputer scienceEvent (computing)business.industrySpeech recognitionComputer Science::Neural and Evolutionary ComputationContext (language use)Pattern recognitionspeech segmentationPerceptronSpeech segmentationSupport vector machineComputer Science::SoundSpeechDetection theoryArtificial intelligencerecognitionHidden Markov modelbusiness
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Application of EαNets to Feature Recognition of Articulation Manner in Knowledge-Based Automatic Speech Recognition

2006

Speech recognition has become common in many application domains. Incorporating acoustic-phonetic knowledge into Automatic Speech Recognition (ASR) systems design has been proven a viable approach to rise ASR accuracy. Manner of articulation attributes such as vowel, stop, fricative, approximant, nasal, and silence are examples of such knowledge. Neural networks have already been used successfully as detectors for manner of articulation attributes starting from representations of speech signal frames. In this paper, a set of six detectors for the above mentioned attributes is designed based on the E-αNet model of neural networks. This model was chosen for its capability to learn hidden acti…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniArtificial neural networkGeneralizationComputer scienceSpeech recognitionSIGNAL (programming language)cognitive architectureFeature recognitionneural networks speech recognitionAnthropomorphic robotsManner of articulationSystems designSet (psychology)Articulation (phonetics)Robots
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