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Record W2168133875 · doi:10.1109/iscas.2005.1465296

Artificial Bandwidth Extension of Telephony Speech by Data Hiding

2005· article· en· W2168133875 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Data Compression Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBandwidth extensionTelephonyComputer scienceExtension (predicate logic)Bandwidth (computing)Speech recognitionTelecommunicationsSpeech codingProgramming language

Abstract

fetched live from OpenAlex

The current public switched telephone network (PSTN) is only able to deliver analog signals in a relatively narrow frequency band, about 300-3400 Hz. Such a bandwidth is so small that the intelligibility of speech frequently suffers from poor subjective quality. In order to improve the voice quality and intelligibility, it is proposed to use a data hiding technique to extend the PSTN channel bandwidth artificially. That is, the higher frequency components beyond the PSTN bandwidth are encoded and imperceptibly embedded into the narrowband signal. When the hidden signal is extracted at the receiver, wideband speech can be reconstructed with better perceptual quality. The advantage of the proposed scheme lies in that it is fully compatible with conventional end-user equipment, e.g., a plain ordinary telephone set (POTS). Experimental results show that the proposed scheme has a better performance than conventional bandwidth extension methods with speaker-independent training.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.625
Threshold uncertainty score0.410

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0020.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.051
GPT teacher head0.317
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations25
Published2005
Admission routes1
Has abstractyes

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