Handling large amounts of data, such as large image databases, requires the use of approximate nearest neighbor search techniques. Recently, Hamming embedding methods such as spec...
In this paper, a new type of metric that defines the similarity between musical audio signals is proposed. Based on the spectral flatness criterion, those metrics achieve low co...
Sub-Nyquist systems capture the signal information in a different fashion than uniform high-rate samples. Consequently, digital processing, which is the prime reason for leaving t...
This paper describes the Arabic broadcast transcription system fielded by IBM in the GALE Phase 3.5 machine translation evaluation. Key advances compared to our Phase 2.5 system ...
George Saon, Hagen Soltau, Upendra Chaudhari, Step...
Predictive coding eliminates redundancy due to correlations between the current and past signal samples, so that only the innovation, or prediction residual, needs to be encoded. ...
We present a new and computationally efficient scheme for classifying signals into a fixed number of known classes. We model classes as subspaces in which the corresponding data...
Phonotactic approach, phone recognition to be followed by language modeling, is one of the most popular approaches to language identification (LID). In this work, we explore how ...
C. P. Santhosh Kumar, Haizhou Li, Rong Tong, Pavel...
The Hidden Markov Model (HMM) has been widely used in many applications such as speech recognition. A common challenge for applying the classical HMM is to determine the structure...
The eigenvalue decomposition (EVD) of a Hermitian matrix in terms of unitary matrices is well known. In this paper, we present an algorithm for the approximate EVD (AEVD) of a par...