Contributed articles presented at the National Seminar on Language and Mind held at Hyderabad in 2004.

The problem which seems to remain with the Advaitin's non-realist account is that in giving up both the robust realist use of existenthood and the strong idealist use of cognitive verification, he seems to have weakened the connection between what must be the case and what is experienced. In explaining the nature of cognition, the realist says that existenthood (objects ontologically independent of cognition)must be the case; the idealist says that existenthoodmust not be the case. But in saying that existenthood (...) and non-existenthood are both outside the purview of the explanation of cognition, and then further, in saying that there is only a weak connection — of coherent assumption or best justification through confirmation — between objects and cognition, in other words, refusing to say whatmust be the case, is the non-realist not making his ontology acutely contingent on the current features of cognition? Is his ontology not, in this sense, provisional upon current cognition? As any reader even glancingly acquainted with Advaita would see straightaway, that understanding of ontology as aprovisional state (samv $$\underset{\raise0.3em\hbox{$\smash{\scriptscriptstyle\cdot}$}}{r} $$ tti-sattā) is precisely what the Advaitin has striven to establish. We must leave the examination of the purpose of this effort for another occasion. (shrink)

Chakravarthi Ram-Prasad's delightful and challenging little book does not fit easily into the standard categories available for academic excursions into philosophy. It is, to simplify, a venture in constructive philosophical theology, centered on questions of being and selfhood, which takes the form of a reflection upon the Bhagavad-gītā commentaries written by two of India's leading philosopher/theologians, Śaṅkara (c. 8th century CE) and Rāmānuja (c. 11th century CE). While Ram-Prasad does try to argue for the best readings of Śaṅkara (...) and Rāmānuja, the book should not be misunderstood as a "merely" historical work. Ram-Prasad looks to the classical thinkers, and indeed the ancient text of the Bhagavad-gītā itself, for enduring insights into the nature of being. It speaks to a number of sub-disciplines within philosophy, including metaphysics, history of philosophy, Indian philosophy, philosophy of religion, and comparative philosophy/theology. (shrink)

Speaker recognition under mismatched conditions is a challenging task. Speech signal is nonlinear and nonstationary, and therefore, difficult to analyze under realistic conditions. Also, in real conditions, the nature of the noise present in speech data is not known a priori. In such cases, the performance of speaker identification or speaker verification degrades considerably under realistic conditions. Any SR system uses a voice activity detector as the front-end subsystem of the whole system. The performance of most VADs deteriorates at the (...) front end of the SR task or system under degraded conditions or in realistic conditions where noise plays a major role. Recently, speech data analysis and processing using Norden E. Huang’s empirical mode decomposition combined with Hilbert transform, commonly referred to as Hilbert–Huang transform, has become an emerging trend. EMD is an a posteriori, adaptive, data analysis tool used in time domain that is widely accepted by the research community. Recently, speech data analysis and speech data processing for speech recognition and SR tasks using EMD have been increasing. EMD-based VAD has become an important adaptive subsystem of the SR system that mostly mitigates the effect of mismatch between the training and the testing phase. Recently, we have developed a VAD algorithm using a zero-frequency filter-assisted peaking resonator and EMD. In this article, the efficacy of an EMD-based VAD algorithm is studied at the front end of a text-independent language-independent SI task for the speaker’s data collected in three languages at five different places, such as home, street, laboratory, college campus, and restaurant, under realistic conditions using EDIROL-R09 HR, a 24-bit wav/mp3 recorder. The performance of this proposed SI task is compared against the traditional energy-based VAD in terms of percentage identification rate. In both cases, widely accepted Mel frequency cepstral coefficients are computed by employing frame processing from the extracted voiced speech regions using the respective VAD techniques from the realistic speech utterances, and are used as a feature vector for speaker modeling using popular Gaussian mixture models. The experimental results showed that the proposed SI task with the VAD algorithm using ZFFPR and EMD at its front end performs better than the SI task with short-term energy-based VAD when used at its front end, and is somewhat encouraging. (shrink)

The performance of most of the state-of-the-art speaker recognition systems deteriorates under degraded conditions, owing to mismatch between the training and testing sessions. This study focuses on the front end of the speaker verification system to reduce the mismatch between training and testing. An adaptive voice activity detection algorithm using zero-frequency filter assisted peaking resonator was integrated into the front end of the SV system. The performance of this proposed SV system was studied under degraded conditions with 50 selected speakers (...) from the NIST 2003 database. The degraded condition was simulated by adding different types of noises to the original speech utterances. The different types of noises were chosen from the NOISEX-92 database to simulate degraded conditions at signal-to-noise ratio levels from 0 to 20 dB. In this study, widely used 39-dimension Mel frequency cepstral coefficient features were used, and Gaussian mixture model–universal background model was used for speaker modeling. The proposed system’s performance was studied against the energy-based VAD used as the front end of the SV system. The proposed SV system showed some encouraging results when EMD-based VAD was used at its front end. (shrink)

In this article, a new adaptive data-driven strategy for voice activity detection using empirical mode decomposition is proposed. Speech data are decomposed using an a posteriori, adaptive, data-driven EMD in the time domain to yield a set of physically meaningful intrinsic mode functions. Each IMF preserves the nonlinear and nonstationary property of the speech utterance. Among a set of IMFs, the IMF that contains source information dominantly called characteristic IMF can be identified and extracted by designing a zero-frequency filter-assisted peaking (...) resonator. The detected CIMF is used to compute energy using short-term processing. Choosing proper threshold, voiced regions in speech utterances are detected using frame energy. The proposed framework has been studied on both clean speech utterance and noisy speech utterance. The proposed method is used for voice activity detection in the presence of white noise and shows encouraging result in the presence of white noise up to 0 dB. (shrink)

This paper and its predecessor () are about the question: 'Are the events in the entire universe encoded in and predictable from any of its parts?' To approach a positive answer in classical physics, the following result is proved and commented on: in Newton's theory of gravitation, the entire trajectory of a particle can be predicted given any segment of it, regardless of how the other particles are moving-provided that there is only a finite number of particles and that their (...) speeds remain bounded. (It is this condition, together with a set of parameters characterising the motion of the other particles, which enables us to estimate the effect of the other particles on the trajectory of the given particle.) The extension of this result to other theories, in particular to special relativity, is discussed. (shrink)