To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure no-reply@cambridge.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Chapter 9 summarizes the main points addressed in previous chapters. The main issues addressed in Chapter 1 are phenomenal prominence, metrical prominence, and the relationship between them. Chapter 2 addresses the Prosodic Hierarchy and structural prominence. Chapter 3 examines the typology of word stress. Chapter 4 examines two correspondence relationships: the relationship between prosodic categories and grid entries and the relationship between syntactic categories and prosodic categories. Directionality effects are addressed in Chapter 5, and grid well-formedness are addressed in Chapter 6. Chapter 7 examines boundary effects, and Chapter 8 focuses on feet.
Default prominence patterns divide into two types: fixed and proportional. In fixed patterns, the number of prominences is constant regardless of the length of the form. Fixed patterns can be single (one prominence per form) or dual (two prominences per form). In proportional patterns, the number of prominences increases as the length of the form increases. Proportional prominence patterns can be either binary (prominence on every second syllable) or ternary (prominence on every third syllable). Phenomenal prominence systems may be either fixed or proportional. Metrical prominence patterns are always proportional. Metrical patterns are typically binary, very rarely ternary. All single and dual phenomenal patterns indicate binary metrical patterns. The simplest binary metrical patterns are the four patterns that exhibit perfect alternation. While each of the four perfect alternation patterns is attested, only a few of the possible departures from perfect alternation are attested. The pattern of attestation exhibits asymmetries that become clear when considering iambic-trochaic mirror image pairs. At most one member of such pairs is attested. With only four reasonably clear examples, ternary stress patterns are extremely rare, and is it impossible to make any significant generalizations about them with any degree of confidence.
The relationship between the metrical grid and the prosodic hierarchy and the relation between prosodic structure and syntactic structure are both relationships and relations of Correspondence. Correspondence is a representational link between two representational objects. Entries on the metrical grid and instances of prosodic categories may correspond, and instances of prosodic categories and instances of syntactic categories may correspond. Mapping is the correspondence relation between instances of prosodic categories and entries on the metrical grid. The mapping relation is one of the key factors influencing the grid’s construction. Mapping is governed by a handful of key principles, including Hierarchy Coordination. The prosodic hierarchy and the metrical grid are both hierarchies and they map to each other as hierarchies. Mapping is required by the violable MAP family of constraints, constraints that require prosodic categories to map to grid entries. The MATCH family of constraints requires faithful correspondence between prosodic categories and syntactic or morphological categories. It requires both that the correspondence relation exist and that that correspondents share key elements. Simple MATCH constraints require correspondents to have exactly the same set of terminal elements. LexMatch constraints require correspondents to have the same set of lexical terminal elements. LexMatch constraints ignore functional terminal elements.
This Element deals with the interplay between phonology, phonetics and acquisition. It addresses the question of whether and how phonological representations are acquired in adult second language (L2) learners in the face of phonetic variation inherent in speech. Drawing from a large number of empirical studies on the acquisition of L2 speech sounds, the Element outlines how phonetic or phonological representations develop in L2 learners on the basis of input in immersion and instructed language learning contexts. Taking in insights from sociophonetics and clinical linguistics, the Element further discusses how accent variation impacts second language phonological acquisition and what clinical studies on individuals with atypical language development can tell us about the nature of phonological representations. Finally, new avenues in the field of L2 phonology are explored, especially with regard to methodological challenges and opportunities related to the use of spontaneous speech and remote data collection.
Uzbek (ISO 639-1: uz) is a Turkic language spoken mainly in Uzbekistan, where the language is accorded the ‘state language’ status (Figure 1). Outside Uzbekistan, ethnic Uzbek populations are scattered across and beyond Central Asia in such countries as Afghanistan, Tajikistan, Kyrgyzstan, Kazakhstan, China, and Saudi Arabia (Balcı, 2004; Yakup, 2020:411). Many Uzbeks in the diaspora speak one or more languages in addition to Uzbek for interethnic communication (Naby, 1984:11). Some ethnic Uzbek communities are reportedly being linguistically assimilated to ethnic groups that are dominant in their countries or regions (Shalinsky, 1979:12–13; Fevzi, 2013:256; Yıldırım, 2019:64). It is therefore unclear exactly what proportion of ethnic Uzbeks retain Uzbek as their first language today. In the case of ethnic Uzbeks in Xinjiang in China, gauging the extent of linguistic assimilation can be difficult because of the limited range of contrasting features that exist between their variety of Uzbek and Uyghur, the interethnic language of Xinjiang, with which it is generally mutually intelligible (Cheng & Abudureheman, 1987:1–2). The varieties of Uzbek spoken in Afghanistan and China have developed autonomously from those spoken within the borders of the former Soviet Union, and hence differ from the present-day standard Uzbek of Uzbekistan, a former Soviet republic, most notably in lexica but also in phonology, morphology, and syntax (Jarring, 1938; Abdullaev, 1979: Reichl, 1983; Cheng & Abudureheman, 1987; Hayitov et al., 1992:36; Gültekin, 2010).
Stress and accent are central to the study of sound systems in language. This book surveys key work carried out on stress and accent and provides a comprehensive conceptual foundation to the field. It offers an up-to-date set of tools to examine stress and accent from a range of perspectives within metrical stress theory, connecting the acoustic phenomenon to a representation of timing, and to groupings of individual speech sounds. To develop connections, it draws heavily on the results of research into the perception of musical meter and rhythm. It explores the theory by surveying the types of stress and accent patterns found among the world's languages, introducing the tools that the theory provides, and then showing how the tools can be deployed to analyse the patterns. It includes a full glossary and there are lists of further reading materials and discussion points at the end of each chapter.
Metrical systems differ in patterns of stress assignment, the domains over which those patterns are built, and acoustic manifestations of stress. It has been widely debated in the phonological/phonetic literature how stress should be represented, what mechanisms govern its assignment, and whether the phonetic underpinnings of primary/secondary stress exist independently of other prominence effects (e.g. boundary strengthening, pitch accents). This Element addresses these fundamental issues on the basis of an in-depth study of a hybrid (lexical-grammatical) metrical system of Ukrainian. It synthesizes previous results with new findings, focusing on the phonetic as well as formal description of the Ukrainian system. The lexical-grammatical stress interactions in Ukrainian pose a challenge for current metrical theories, shed light on the relation between the lexical and grammatical stress domains, and the relationship between categorical and gradient aspects of the metrical system. This title is also available as Open Access on Cambridge Core.
San Martín Peras Mixtec (autonym: Tu’un Nta’vi or Tu’un Savi) is an Otomanguean language spoken by roughly 11,500 people in the municipality of San Martín Peras, in Oaxaca, Mexico (Instituto Nacional de Estadística y Geografía, 2020), as shown in Figure 1. The municipality is in the district of Juxtlahuaca, bordering the state of Guerrero. As of 2020, approximately 97% of the population of the municipality over three years old is a speaker of an Indigenous language. Of those that speak an Indigenous language, approximately 60% also speak Spanish, meaning that around 37% of the total population is monolingual in Mixtec (Instituto Nacional de Estadística y Geografía, 2020). Despite these figures, it is difficult to estimate the total number of native speakers of the language, as many community members have migrated to other parts of Mexico and the United States, especially to several towns in California (Mendoza, 2020).
San Juan Piñas Mixtec (endonym: Tò’ō Ndá’ví; henceforth SJPM) (ISO 639-3: vmc) is a previously undocumented Oto-Manguean language of the Mixtecan branch spoken in the municipality of Santiago Juxtlahuaca in Oaxaca, Mexico (shown in the map in Figure 1). According to a 2020 census conducted by the Mexican government (INEGI 2020), there are 717 inhabitants in the town of San Juan Piñas, almost all of whom speak SJPM as their native language. Additionally, speakers are found in diaspora communities in the western states of Baja California (Mexico), California, Oregon, Washington, and other places in Mexico and the United States. There are about half a million speakers of all Mixtec varieties in Mexico (INEGI 2020), and between 100,000 and 150,000 speakers of Mixtec in California (Kresge 2007). While elderly speakers in San Juan Piñas tend to be monolingual, younger speakers are bilingual in SJPM and Spanish. In diaspora communities in the United States, younger SJPM speakers shift to English and/or Spanish as their primary language(s) of communication.
Zhongjiang Chinese (中江话) is a variety of Mandarin Chinese, one of the ten language families in China (Mandarin, Cantonese, Xiang, Min, Gan, etc.,). Sometimes the term “Mandarin” is also used to refer to the national lingua franca “Putonghua”. We refer to the national lingua franca as “Standard Mandarin” and reserve the term Mandarin (官话) to refer to the language family, as distinct from other families, e.g., Cantonese, Xiang, Min, Gan, etc. Within Mandarin, Zhongjiang is a member of the Southwestern dialects (西南官话) (Language Atlas of China 1988). It is spoken in the urban areas of Zhongjiang county (中江县) in Sichuan province (四川省 ) of China. Zhongjiang county belongs to the Deyang (德阳) region, which is located in the middle of Sichuan province, about 100 kilometers northeast from the provincial capital of Chengdu (成都). Zhongjiang is just beyond the Chengdu Plain (成都平原), so the terrain is mostly hilly, with little flat land. It has a population of 1.37 million residents and an area of 2,200km2 (data from Zhongjiang official website, updated July 7, 2021).
This study tests the hypothesis that alternation patterns with strong lexical support are more robust than those with no, or weak, lexical support. Focusing on three alternation patterns in Korean with varying productivity and generality, we measured lexical support in two ways. First, we conducted an acceptability-rating experiment investigating Korean speakers’ judgements on non-words with and without violations of the phonotactic constraints motivating the alternations. In addition, we performed a simulation of learning a maximum entropy (MaxEnt) Harmonic Grammar from a dictionary corpus. The results of the experiment and computational modelling confirmed the hypothesis by showing that if an alternation is robust, its associated phonotactic constraint is learned with a high weight from the MaxEnt simulation, and it affects the participants’ well-formedness ratings for non-words. Consequently, the results of this research support the claim of a tight link between alternations and phonotactics.