New Italian Toolkit Brings Standardized Speech Analysis to Neurological Patients Beyond English

When a stroke or a neurodegenerative disease disrupts a person’s language, the speech that spills out—halting, garbled, emptied of nouns—carries clinical information of extraordinary diagnostic value. For decades, researchers have mined such connected speech for markers of aphasia, primary progressive aphasia, Alzheimer’s disease, and Parkinson’s disease. But the tools they use to transcribe and code that speech were built primarily for English, and a growing body of evidence shows that the symptoms of neurological language disorders do not translate cleanly across languages. A new open-access study published in Behavior Research Methods now offers a detailed, structured solution for Italian, one of the world’s most studied yet linguistically distinct languages, in the form of a complete adaptation of the dominant standardized speech annotation system.

The toolkit, developed by Allegra Benzini, Alyssa M. Lanzi, Cinzia Palmirotta, Simona Aresta, Petronilla Battista, and Gaia C. Santi of the Istituti Clinici Scientifici Maugeri IRCCS and the University of Delaware, extends the CHAT transcription conventions and the CLAN analysis software developed within the CHILDES/TalkBank framework to Italian-speaking adults with neurological disorders. CHAT—Codes for the Human Analysis of Transcripts—and its companion program CLAN have long been the backbone of quantitative language analysis, implemented in 28 languages and applied to a database of more than 44 million spoken words. Yet the system was originally designed around English child language, and its conventions presuppose English grammar, English phonology, and English clinical presentation. The Italian adaptation, presented as a downloadable operational manual, systematically reshapes those conventions to fit the structure of Italian and the realities of aphasic speech.

The methodological heart of the work is a transparent decision tree applied to every symbol in the CHAT manual. Each of the 59 transcription symbols was evaluated symbol by symbol against explicit inclusion and exclusion criteria: symbols had to be relevant to adult clinical populations and to linguistic phenomena associated with neurologically based language disorders such as post-stroke aphasia, mild cognitive impairment, primary progressive aphasia, Parkinson’s disease, and Alzheimer’s disease. Symbols dedicated to child language development or to conversational analysis notation irrelevant to adult neurological speech were excluded from consideration from the start. The outcome of that evaluation was decisive: 40 symbols were retained unchanged, 15 were removed, four were adapted for Italian, and one was newly created. A parallel process addressed the 11 error-coding symbols, of which six were retained, four were adapted, and one new marker was introduced, with no symbols eliminated outright.

Many of the removals follow directly from the architecture of Italian. As a syllable-timed language, Italian does not systematically encode secondary stress at the lexical level, so the secondary stress marker was dropped. Vowel lengthening, common in Italian and heavily influenced by non-pathological dialectal variation, would confound clinical interpretation, so the lengthened-syllable marker went as well. Punctuation symbols such as the comma, semicolon, and colon were excluded because they neither define units of analysis nor influence automated CLAN outputs such as mean utterance length. The multiple-repetition marker was deemed redundant, already captured by the existing repetition symbol, and the unclear retracing notation was removed because it served only conversion to a competing transcription system. These are small deletions, but together they strip the transcription of artifacts that would otherwise inject noise into quantitative measures of Italian speech.

The adaptations cut deeper. In English, the omission of subjects, auxiliaries, or function words is typically a grammatical violation, so the original CHAT system codes such omissions with an error marker. Italian, however, is a null-subject language: dropping the pronoun in a phrase like “ha gli occhiali da sole”—literally “has the sunglasses”—is perfectly grammatical. The Italian toolkit therefore restricts the omitted-word marker to contexts where omission genuinely violates Italian grammar, and limits the grammatical error marker to utterances whose well-formedness fails by Italian, not English, standards. The clause delimiter was likewise repurposed to tag subordinate clauses, giving clinicians a direct metric of syntactic complexity that the English system computes automatically but that had no Italian equivalent—critical for characterizing the telegraphic, agrammatic output of many aphasic patients.

Phonological error coding underwent a deliberate simplification. The extensive English taxonomy of phonological error subtypes was collapsed into two operational categories: one for recognizable phonological errors such as omissions, substitutions, insertions, and metatheses, and one for phonological neologisms—complete losses of the intended target that may co-occur with non-word transcription symbols. Morphological coding was similarly tailored to the Italian inflectional system, split into markers for agreement errors of gender, number, and person, and for errors of verbal morphology including tense, mood, and irregular inflections. Because Italian verbs carry their grammatical freight in rich inflectional endings rather than in separate auxiliary words, morphological errors reveal a different facet of aphasia in Italian than they do in English.

Two entirely new symbols fill gaps that became glaring in clinical practice. The first, a word fragment marker, captures partial word productions that are abandoned without reformulation and without a precisely recognizable lexical target—a phenomenon the authors note is frequent in adult neurological speech and central to the lexical retrieval difficulties that constitute the most common aphasic disorder. The second, an articulatory distortion marker, codes phonetic distortions in which sounds are mangled despite correct phonological sequencing, a hallmark of motor speech impairments such as apraxia of speech and dysarthria. The original English system could represent such behaviors structurally, but could not quantify them at the error-coding level, even though distinguishing dysarthria from apraxia of speech from phonological difficulty is essential for differential diagnosis in the clinic.

To demonstrate the toolkit’s discriminative power, the researchers applied it to a connected speech sample from a 64-year-old right-handed woman with the non-fluent variant of primary progressive aphasia, a condition defined by effortful, agrammatic, often barely intelligible speech. Her sample, elicited with the picture-description task of the Screening for Aphasia in Neurodegeneration, was transcribed in Italian with the adapted conventions and compared with its English translation transcribed under the original CHAT rules. The side-by-side comparison exposes how the same clinical behavior is encoded differently depending on the language of analysis: the Italian transcript flags articulatory distortions, repeated phonological fragments, and retracing sequences through the new markers, while the English transcript must insert a null subject and assign a grammatical error code to subject omission that is simply licensed grammar in Italian. Compound nouns provide a further illustration, since English compounds rely on hierarchical stress patterns that Italian lexical items, carrying a single primary stress, do not.

Beyond the immediate benefit to Italian clinicians and researchers, the study stakes out a broader claim about how speech analysis should travel across languages. The authors emphasize that the majority of the world’s population does not speak English, yet research and clinical tools remain overwhelmingly Anglophone, and directly transferring English instruments often fails for diagnosis, treatment, and cross-cultural comparison. Their prior cross-linguistic work comparing healthy speakers of English, Italian, Cantonese, and Mandarin found significant differences in function word use and phonology that reflect language-specific morphosyntactic rules, reinforcing the point that linguistic diversity shapes the very manifestation of language processing patterns. The Italian toolkit therefore aims at a balance: preserving the conceptual organization and operational principles of TalkBank so that data remain comparable across languages, while introducing targeted adjustments grounded in the structure of Italian. It is designed as a flexible resource in which users select coding options guided by specific clinical or research goals, whether at the word or sentence level, or across the phonetic–phonological, lexical–semantic, morphosyntactic, and pragmatic domains.

The authors are candid about limitations. The adaptation targets adult speakers with neurological disorders and does not address developmental populations, where further modifications would be needed; coding remains time-consuming and may constrain large-scale implementation; and the morphosyntactic annotation layer—the %mor and %pos tiers—was deliberately left untouched, since adapting it requires alignment with both Italian grammar and specific research hypotheses. Future work, they suggest, should explore tighter integration between standardized coding schemes and automated transcription approaches such as Whisper-based speech recognition. Still, the toolkit stands as a replicable model for extending standardized annotation systems to any structurally distinct language, a necessary step if the rapidly advancing field of speech-based neurological biomarkers is to serve patients in the languages they actually speak.

Subject of Research: Cross-linguistic adaptation of standardized speech transcription and coding tools for assessing neurological language disorders in Italian-speaking adults.

Article Title: Extending standardized speech analysis across languages: An Italian toolkit for transcription and coding of neurological speech

Article References: Benzini, A., Lanzi, A. M., Palmirotta, C., Aresta, S., Battista, P., & Santi, G. C. (2026). Extending standardized speech analysis across languages: An Italian toolkit for transcription and coding of neurological speech. Behavior Research Methods, 58(10), Article 292. https://doi.org/10.3758/s13428-026-03175-x

Image Credits: AI Generated

DOI: 10.3758/s13428-026-03175-x

Keywords: speech analysis, CHAT, CLAN, TalkBank, aphasia, primary progressive aphasia, cross-linguistic adaptation, Italian language, neurodegenerative disease, connected speech, language annotation, behavior research methods