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Enregistrement W4230999539 · doi:10.1080/03069400.2014.914732

Training the Dragon®: the use of voice recognition software in the legal writing classroom

2014· article· en· W4230999539 sur OpenAlexaboutno aff
Maureen B. Collins

Notice bibliographique

RevueThe Law Teacher · 2014
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueArtificial Intelligence in Law
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésTraining (meteorology)SoftwareComputer sciencePsychologySpeech recognitionMultimediaProgramming languageGeography

Résumé

récupéré en direct d'OpenAlex

AbstractWe are surrounded by technology – most of it designed to make our personal and professional lives easier. We have voice-assisted software at our fingertips. One conversation with Siri® and we know where to dine or who starred in our favorite movie. In the legal profession, technology is used not only to process words, but to conduct legal research, manage voluminous litigation documents, and track information on opposing counsel. Surely, then, there is a place for technology in the legal writing process. AcknowledgementsThe author extends her gratitude to Chandra Critchelow for her excellent research and assistance in the preparation of this article. She also thanks Michael Eisnach and Professor Julie Spanbauer for their editorial assistance and the John Marshall Law School for its support of research efforts.Notes1 See e.g. D. Hope, Voice Recognition Software Dictation Test (2013) at http://voice-recognition-software-review.toptenreviews.com/voice-recognition-software-dictation-test.html (accessed 3 February 2014) ("Dragon NaturallySpeaking is the most well-known name in voice recognition software"). Nuance Communications, http://www.nuance.com/for-healthcare/index.htm; http://www.nuance.com/for-business/by-industry/legal/index.htm (accessed 30 January 2014).2 Note Speech/Text Notepad by Khymaera is an example of a free downloadable application for Android platforms, found on the GooglePlay store. Voice Texting Pro by Sparkling Apps is an example of a free downloadable application for the iPhone/iPad/iPod touch platforms found on the iTunes store.3 Nuance's Dragon® Medical is one example of specialized VRS software for the medical profession. Nuance Communications, http://www.nuance.com (accessed 22 January 2014).4 AT & T's Bell Labs produced the first electronic speech synthesizer in 1936. The machine, demonstrated at the 1939 World's Fair, used a keyboard and foot pedals. The 1970s saw developments in the field when the Hidden Markov Modeling approach was invented by Lenny Baum of Princeton University. The HMM system became the basis for modern day VRS technology. In 1978, Texas Instruments introduced the popular children's toy "Speak and Spell". In 1982, Dragon Systems was founded by speech industry pioneers Drs. Jim and Janet Baker. Dragon released its first word dictation level speech recognition software in 1995.5 Most smartphones and tablets come with voice recording software already installed. There are many free applications in the iTunes app and Google Play stores. Macintosh computers feature a pre-installed voice recording system as part of the iLife package (called Garage Band) and the Windows operating systems have built-in VRS named SoundRecorder.6 Supra n. 1. Some additional types of applications include Siri Personal Assistant® for the Apple operating system and Google's cross-platform Voice Search for the Android operating system.® Siri Personal Assistant, http://www.apple.com/ios/siri/ (accessed 31 January 2014)‎; Google Voice Search, http://www.google.com/mobile/voice-search/ (accessed 31 January 2014).7 The training process helps the software personalize interpretation of the spoken word. The initial training process takes place before you begin using the software. You may be asked to identify your age, gender and regional origin. You will be asked to read one of the proscribed pieces of literature (from a children's book to Kennedy's inaugural address) for up to four minutes. You can add frequently used words to the VRS vocabulary with additional training.8 The oral commands can be used to navigate through the computer, or for editing in documents.9 Nuance Communications, http://www.nuance.com/for-healthcare/index.htm; http://www.nuance.com/for-business/by-industry/legal/index.htm (accessed 30 January 2014).10 See generally, J.J. Pavlick Jr. and R. Pearson, "Implementing the New 508 Standards for the Disabled" (2001) Procurement Lawyer 1; J. Jolly-Ryan, "Disabilities to Exceptional Abilities: Law Students with Disabilities, Nontraditional Learners, and the Law Teacher as a Learner" (2005) 6 Nevada Law Journal 116.11 Nuance Communications, http://www.nuance.com/for-business/by-industry/education/dragon-education-solutions/index.htm (accessed 30 January 2014).12 Ibid.13 Ibid.; Wikipedia, http://www.wikipedia.com (search for "Voice Recognition Software") (accessed 30 January 2014).14 Wikipedia, http://www.wikipedia.com (search for "Voice Recognition Software") (accessed 30 January 2014); Nuance Communications, http://www.nuance.com/for-business/index.htm#!ind_sol_list (accessed 30 January 2014).15 B.J. Everson, "Vygotsky and the Teaching of Writing" (1991) 13(3) The Quarterly 8–11.16 Ibid.17 Ibid.18 Ibid.19 VRS is also available in a variety of languages. A student more comfortable brainstorming or composing in her native Mandarin could do so, and then use the product to serve as a basis for a "translation" of the product into English.20 B.S. Flowers, "Madman, Architect, Carpenter, Judge: Roles and the Writing Process" (1981) 58 Language Arts 834, pp. 834–836.21 Ibid.22 Ibid.23 Ibid.24 Ibid.25 Ibid.26 The seven most common types of language-based disorders are: dyslexia, dysgraphia, dyscalculia, central auditory processing disorder, non-verbal learning disorder, visual processing disorder, and dysphagia. Learning Ally, www.learningally.com (accessed 28 January 2014). Dyslexia, a reading-based disorder that causes reading comprehension problems by inverting the order of letters, is the best known of these disorders.27 Ibid.28 Americans with Disabilities Act of 1990, 42 USC §12101 et seq.; Equality Act 2010.29 www.usnews.com/education/best-graduate-schools/top-law-schools (accessed 28 January 2014).30 I. Leki and J. Carson, "Completely Different Worlds: EAP and the Writing Experiences of ESL Students in University Courses" (1997) 31 TESOL Quarterly 39, pp. 39–40, 54; T. Silva, "L1 vs. L2 Writing: ESL Graduate Students' Perceptions" (1992) 10 TESL Canada Journal 27–47.31 L.J. Solomon and E.D. Rothblum, "Academic Procrastination: Frequency and Cognitive-Behavioral Correlates" (1984) 31 Journal of Counseling Psychology 503; W. van Eerde, "A Meta-analytically Derived Nomological Network of Procrastination" (2003) 35 Personality and Individual Differences 1401.32 Ibid.33 G. Beswick, E.D. Rothblum and L. Mann, "Psychological Antecedents of Student Procrastination" (1988) 23 Australian Psychologist 207.34 A. Ellis and W.J. Knaus, Overcoming Procrastination (New York, Institute for Rational Living, 1977).35 S. Brownlow and R.D. Reasinger, "Putting off until Tomorrow What Is Better Done Today: Academic Procrastination as Function of Motivation toward College Work" (2000) 15 Journal of Social Behavior and Personality 15.36 Ibid.37 P. Steel, "The Nature of Procrastination: A Meta-Analytic and Theoretical Review of Quintessential Self-Regulatory Failure" (2007) 133 Psychological Bulletin 65 ("the prevalence and availability of temptation, for example, in the forms of computer gaming or internet messaging, should continue to exacerbate the problem of procrastination").38 I.L. Janis and L. Mann, Decision-Making: A Psychological Analysis of Conflict, Choice, and Commitment (New York, Free Press, 1977).39 J.R. Ferrari, "A Preference for a Favorable Public Impression by Procrastinators: Selecting Among Cognitive and Social Tasks" (1991) 12 Personality and Individual Differences 1233; J.R. Ferrari, "Psychometric Validation of Two Procrastination Inventories for Adults: Arousal and Avoidance Measures" (1992) 14 Journal of Psychopathology and Behavioral Assessment 97.40 C. Senecal, R. Koestner and R. Vallerand, "Self-regulation and Academic Procrastination" (1995) 135 Journal of Social Psychology 607.41 Beswick et al., supra n. 33.42 E.D. Rothblum, L.J. Solomon and J. Murakami, "Affective, Cognitive and Behavioral Differences Between High and Low Procrastinators" (1986) 33 Journal of Counseling Psychology 387; K.L. Ferguson and M.R. Rodway, "Cognitive Behavioral Treatment of Perfectionism: Initial Evaluation Studies" (1994) 4 Research on Social Work Practice 283.43 C. Fischer, "Read this Paper Later: Procrastination with Time-consistent Preferences" (2001) 46 Journal of Economic Behavior & Organization 249.44 Brownlow and Reasinger, supra n. 35, at p. 16.45 Ferrari, "Preference for Favorable Public Impression" and "Psychometric Validation", supra n. 39.46 Janis and Mann, supra n. 38.47 Beswick et al., supra n. 33.48 J. Stoeber and J.H. Childs, "The Assessment of Self-oriented and Socially Prescribed Perfectionism: Subscales Make a Difference" (2010) 92 Journal of Personality Assessment 577.49 Ibid.50 A. Onwuegbuzie, "Academic Procrastinators and Perfectionist Tendencies among Graduate Students" (2000) 15 Journal of Social Behavior & Personality 103.51 C.H. Lay and C.H. Schouwenburg, "Trait Procrastination, Time Management, and Academic Behavior" (1993) 8 Journal of Social Behavior and Personality 647; D.M. Tice and R.F. Baumeister, "Longitudinal Study of Procrastination, Performance, Stress, and Health: The Costs and Benefits of Dawdling" (1997) 8 Psychological Science 454.52 Ibid.53 Ibid.54 A. Johnstone, "The Writer's Hell: Approaches to Writer's Block" (1983) 2 Journal of Teaching Writing 155.55 E. Valarino and G. Yaber, "Overcoming Researcher's Block Symptoms: Creative Strategies for Research" (2002) 36 Interamerican Journal of Psychology 63.56 R. Boice, "Increasing the Writing Productivity of 'Blocked' Academicians" (1982) 20 Behavioral Research and Therapy 197; see also Johnstone, supra n. 54.57 M. Rose, "Rigid Rules, Inflexible Plans and the Stifling of Language: A Cognitivist Analysis of Writer's Block" (1980) 31 College Composition and Communication 389.58 Ibid.59 Ibid.60 Ibid.61 Ibid.62 In such cases, the institution should be obligated to pay for the software and associated expenses.63 See Appendix A.64 Headsets are often included with the software package. I recommend, though, that you consider investing a small amount (approximately $20) in a better headset to improve the quality of the transcription.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,006
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,708
Score d'incertitude au seuil0,989

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0060,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,001
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,244
Tête enseignante GPT0,360
Écart entre enseignants0,116 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2014
Routes d'admission1
Résumé présentoui

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