the quality of the communication between teachers and students and ultimately, of classroom education itself, is closely linked to the acoustic quality of the auditorium. this acoustic quality can be characterized based on the reverberation time (rt), speech transmission index (sti) and the sound insulation. in this context, an acoustic study was conducted in an auditorium located in the higher...

Harmonic plus noise model (HNM) divides the speech spectrum in two bands: harmonic and noise. As most of the non-periodic components are removed in harmonic part, it may be expected that HNM synthesis is less susceptible to additive noise in input speech. As HNM analysis/synthesis is performed at each glottal closure instant (GCI), errors in estimation of GCIs affect the quality of the synthesi...

Water contamination is indeed a worldwide problem that threatens public health, environmental protection, and agricultural productivity. The distinctive attributes of machine learning (ML)-based modelling can provide in-depth understanding into increasing water quality challenges. This study presents the development multi-expression programming (MEP) based predictive model for parameters, i.e.,...

As broadband and high-speed IP networks spread, IP-telephony services have become a popular speech communication application over IP networks. Recently, the speech quality of IP-telephony services has become close to that of conventional PSTN services. To provide better speech quality to users, speech communication with wider bandwidth (e.g., 7 kHz) is one of the most promising applications. To...

Community indices, such as maturity or diversity, condense information regarding the structure and composition of communities into a single metric. Soil health and quality can be inferred from such indices by assuming that communities with different structure and composition function differently. Thus, these indices can be instrumental in monitoring soil and sediment quality as well as assessin...

The Informedia Digital Video Library Project at Carnegie Mellon University [1] combines speech, image and natural language understanding to automatically transcribe, segment and index video for intelligent search and image retrieval. Since 1995, thousands hours of video (over two terabytes of data) have been collected, with automatically generated metadata and indices for retrieving videos from...