4 accepted papers
Speaker diarization tells who spoke and when? in an audio stream. SincNet is a recently developed novel convolutional neural network (CNN) architecture where the first layer consists of parameterized sinc filters. Unlike conventional CNNs, SincNet take raw speech waveform as input. This paper levera…
In certain applications such as zero-resource speech processing or very-low resource speech-language systems, it might not be feasible to collect speech activity detection (SAD) annotations. However, the state-of-the-art supervised SAD techniques based on neural networks or other machine learning me…
A new method to analyze and classify daily activities in personal audio recordings (PARs) is presented. The method employs speech activity detection (SAD) and speaker diarization systems to provide high level semantic segmentation of the audio file. Subsequently, a number of audio, speech and lexica…
The ability to estimate the number of words spoken by an individual over a certain period of time is valuable in second language acquisition, healthcare, and assessing language development. However, establishing a robust automatic framework to achieve high accuracy is non-trivial in realistic/natura…