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Record W2163485475 · doi:10.1109/ccnc.2007.74

Combining VoiceXML with CCXML: A Comparative Study

2007· article· en· W2163485475 on OpenAlexaff
Daniel Amyot, Renato Simões

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSpeech and dialogue systems
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsComputer scienceSession Initiation ProtocolMarkup languageVoice over IPProtocol (science)SIP trunkingComponent (thermodynamics)Session (web analytics)Simple (philosophy)AbstractionWorld Wide WebMultimediaXMLServerThe Internet

Abstract

fetched live from OpenAlex

Many Interactive Voice Response (IVR) systems use the popular VoiceXML standard for managing vocal dialogs. For call control aspects, such systems often use the Session Initiation Protocol (SIP) or a similar protocol. W3C is currently developing a new Call Control eXtensible Markup Language (CCXML) standard, at a higher abstraction level than SIP and which could hide the latter in order to accelerate the development of complex VoIP solutions that have an IVR component. But will this really be the case? This paper presents a comparative study base on a simple Personal Assistant system. Although there are undeniable benefits to a CCXML-VoiceXML approach, many observations and lessons lead us to believe that developers will face several limitations and potential pitfalls.

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.

How this classification was reachedexpand

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.558
Threshold uncertainty score0.284

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.036
GPT teacher head0.292
Teacher spread0.256 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2007
Admission routes1
Has abstractyes

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