11 citations · 15 across the 8 of their papers we have counts for
8 papers
Direction of arrival estimation from distant microphone data using single frequency filtering
Sushmita Thakallapalli, Sudarsana Reddy Kadiri, Nilesh Madhu +1
In distant microphones, broadband (BB) methods for direction-of-arrival (DoA) estimation are more suitable than narrowband (NB) methods. Due to the aggregation of their optimizatio…
Intelligibility of Speech in Noise: Investigating Contribution of Magnitude and Phase Spectra
Bhanu Teja Nellore, Sudarsana Reddy Kadiri, Rohit Kumar +2
It is well known that intelligibility of speech reduces in the presence of ambient noise. However, studies show that all sounds are not affected uniformly (or equally) and that vow…
Single frequency filtering based multi-speaker direction of arrival estimation from stereo recordings
Sushmita Thakallapalli, Sudarsana Reddy Kadiri, Nilesh Madhu +1
Robust direction-of-arrival (DoA) estimation from noisy and reverberant microphone signals remains challenging. Conventional estimators such as generalized cross-correlation (GCC)…
SPRING-INX: A Multilingual Indian Language Speech Corpus by SPRING Lab, IIT Madras
Nithya R, Malavika S, Jordan F +8
India is home to a multitude of languages of which 22 languages are recognised by the Indian Constitution as official. Building speech based applications for the Indian population…
A Bayesian Multilingual Document Model for Zero-shot Topic Identification and Discovery
Santosh Kesiraju, Sangeet Sagar, Ondřej Glembek +3
In this paper, we present a Bayesian multilingual document model for learning language-independent document embeddings. The model is an extension of BaySMM [Kesiraju et al 2020] to…
Learning document embeddings along with their uncertainties
Santosh Kesiraju, Oldřich Plchot, Lukáš Burget +1
Majority of the text modelling techniques yield only point-estimates of document embeddings and lack in capturing the uncertainty of the estimates. These uncertainties give a notio…
Statistical Parametric Speech Synthesis Using Bottleneck Representation From Sequence Auto-encoder
Sivanand Achanta, KNRK Raju Alluri, Suryakanth V Gangashetty
In this paper, we describe a statistical parametric speech synthesis approach with unit-level acoustic representation. In conventional deep neural network based speech synthesis, t…
Significance of Maximum Spectral Amplitude in Sub-bands for Spectral Envelope Estimation and Its Application to Statistical Parametric Speech Synthesis
Sivanand Achanta, Anandaswarup Vadapalli, Sai Krishna R. +1
In this paper we propose a technique for spectral envelope estimation using maximum values in the sub-bands of Fourier magnitude spectrum (MSASB). Most other methods in the literat…