Slide Set 10-Tone Representation and Derivation-F2024

Tone: Representation and Derivation

1. Introduction to Features and Segments

  • Two views regarding segments:

    • Bundled Features View: Segments composed of features bundled in a matrix (e.g., +F1 and -F1)

    • Autonomous Features View: Segments defined by distinct, independent features

2. Implications of Feature Autonomy

  • Autonomy means shared features affect all segments with that feature:

    • Example: A rule for a feature impacts all segments sharing it.

    • Features can be maintained even if the associated segment is lost.

    • Rules may require identical feature specifications across sequences of segments.

    • Rules may prohibit sequences from sharing identical labels.

  • Evidence from Tone: Tone reinforces the autonomous nature of features against the view of independent feature matrices.

3. Understanding Tone Languages

  • Definition: A tone language uses pitch contrastively to differentiate meaning between morphemes.

  • Types of Tone Languages:

    • Register Tone Languages:

      • Utilize level tones (e.g., high, mid, low)

      • May also feature contour tones derived from level tones.

      • Example: Nupe (Volta-Niger):

        • Level:

          • High: ba + H (bitter)

          • Mid: ba + M (cut)

          • Low: ba + L (count)

        • Contour:

          • Rising: ba + LH (indeed)

          • Falling: ba + HL (defamation)

    • Contour Tone Languages:

      • Have both contour and level tones but contour tones are not based on level tones.

      • Example: Mandarin:

        • ma + high level (55) 'mother'

        • ma + rising (35) 'hemp'

        • ma + falling-rising (214) 'horse'

        • ma + falling (51) 'scold'

  • Focus Area: This lecture emphasizes register tone languages.

4. Tone Identification in Register Tone Languages

  • Tone Features:

    • Tones distinguished by three features: High (H), Mid (M), Low (L).

    • Contour tones can represent pitch variation (e.g., HL, LH).

  • Tone Transcription Conventions:

    • Level tones:

      • H: bá (high)

      • L: bà (low)

    • Contour tones:

      • HL (falling): bâ

      • LH (rising): bǎ

      • M: bā or ba (mid)

  • Tone-Bearing Units (TBUs):

    • Typically vowels bear tones, but some consonants can as well.

    • Example: Efik (Benue-Congo):

      • èdèp ‘you (sg) buy’

      • édèp ‘s/he buys’

      • ńdèp ‘I buy’

5. Autosegmental Representation of Tones

  • Autosegmental Phonology:

    • Tones not represented in a linear manner; they occupy a separate tier from other features.

    • Association Lines:

      • Show connections between tonal features and segments, allowing for complex mappings.

6. Examining Relations in Mende

  • Examples of tone relationships:

    • One-to-One: [ŋ͡ɡílà] 'dog'

    • One-to-Many: [pɛ́lɛ́] 'house' (single H)

    • Many-to-One: [m͡bû] 'owl' & [m͡bǎ] 'rice'

7. Underlying Specifications of Tones

  • Underlying Representations: Each morpheme identified with a tone or toneless.

  • Floating Tones: Not directly linked to segments, e.g., /ma, L/

  • Prespecified Tones: Indicate tone tied to a specific segment, e.g., /ma-L/

8. Universal Association Convention (UAC)

  • Key Principles:

    • Tones associated with TBUs one-to-one, left-to-right or right-to-left.

    • Association lines must not cross (No Crossing Constraint).

    • Parameters leading to tone spreading (sharing) or tone docking (creating contour tones).

    • Each TBU must link with at least one tone (or more).

9. OCP and Derivations in Tone Languages

  • Obligatory Contour Principle (OCP): Identical adjacent tones prohibited within a morpheme or word,

  • OCP Outcomes: Represents various conflicts in derived forms needing resolution.

10. Repairing the OCP

  • Options for OCP Repairs:

    • Substitution: Adjusting tones to prevent adjacency violations.

    • Deletion: Removing tones to align with OCP requirements.

  • Example Cases:

    • Mende tone patterns highlight strategies for managing adjacent identical tones, demonstrating rules and derivations clear through structure.

Conclusion

  • Tones in register tone languages demonstrate the complex navigation between representation, rules, and phonological behaviors that reveal deeper structural functionalities of language.