Ejemplo n.º 1
0
def corpus_data_ur_sr():
    levels = [SegmentTier('sr', 'phone'),
              OrthographyTier('word', 'word'),
              TranscriptionTier('ur', 'word')]
    srs = [('k', 0.0, 0.1), ('ae', 0.1, 0.2), ('s', 0.2, 0.4),
           ('aa', 0.5, 0.6), ('r', 0.6, 0.7),
           ('k', 0.8, 0.9), ('u', 0.9, 1.1),
           ('d', 2.0, 2.1), ('aa', 2.1, 2.2), ('g', 2.2, 2.25),
           ('ah', 2.25, 2.3), ('z', 2.3, 2.4),
           ('aa', 2.4, 2.5), ('r', 2.5, 2.6),
           ('t', 2.6, 2.7), ('uw', 2.7, 2.8),
           ('ay', 3.0, 3.1),
           ('g', 3.3, 3.4), ('eh', 3.4, 3.5), ('s', 3.5, 3.6)]
    words = [('cats', 0.0, 0.4), ('are', 0.5, 0.7), ('cute', 0.8, 1.1),
             ('dogs', 2.0, 2.4), ('are', 2.4, 2.6), ('too', 2.6, 2.8),
             ('i', 3.0, 3.1), ('guess', 3.3, 3.6)]
    urs = [('k.ae.t.s', 0.0, 0.4), ('aa.r', 0.5, 0.7), ('k.y.uw.t', 0.8, 1.1),
           ('d.aa.g.z', 2.0, 2.4), ('aa.r', 2.4, 2.6), ('t.uw', .6, 2.8),
           ('ay', 3.0, 3.1), ('g.eh.s', 3.3, 3.6)]
    levels[0].add(srs)
    levels[1].add(words)
    levels[2].add(urs)

    hierarchy = Hierarchy({'phone': 'word', 'word': None})
    parser = BaseParser(levels, hierarchy)
    data = parser.parse_discourse('test_ursr')
    return data
Ejemplo n.º 2
0
def corpus_data_syllable_morpheme_srur():
    levels = [SegmentTier('sr', 'phone', label=True),
              TranscriptionTier('ur', 'word'),
              GroupingTier('syllable', 'syllable'),
              MorphemeTier('morphemes', 'word'),
              OrthographyTier('word', 'word'),
              GroupingTier('line', 'line')]

    srs = [('b', 0, 0.1), ('aa', 0.1, 0.2), ('k', 0.2, 0.3), ('s', 0.3, 0.4),
           ('ah', 0.4, 0.5), ('s', 0.5, 0.6),
           ('er', 0.7, 0.8),
           ('f', 0.9, 1.0), ('er', 1.0, 1.1),
           ('p', 1.2, 1.3), ('ae', 1.3, 1.4), ('k', 1.4, 1.5), ('eng', 1.5, 1.6)]
    urs = [('b.aa.k.s-ah.z', 0, 0.6), ('aa.r', 0.7, 0.8),
           ('f.ao.r', 0.9, 1.1), ('p.ae.k-ih.ng', 1.2, 1.6)]
    syllables = [(0, 0.3), (0.3, 0.6), (0.7, 0.8), (0.9, 1.1),
                 (1.2, 1.5), (1.5, 1.6)]
    morphemes = [('box-PL', 0, 0.6), ('are', 0.7, 0.8),
                 ('for', 0.9, 1.1), ('pack-PROG', 1.2, 1.6)]
    words = [('boxes', 0, 0.6), ('are', 0.7, 0.8),
             ('for', 0.9, 1.1), ('packing', 1.2, 1.6)]
    lines = [(0, 1.6)]

    levels[0].add(srs)
    levels[1].add(urs)
    levels[2].add(syllables)
    levels[3].add(morphemes)
    levels[4].add(words)
    levels[5].add(lines)

    hierarchy = Hierarchy({'phone': 'syllable', 'syllable': 'word',
                           'word': 'line', 'line': None})
    parser = BaseParser(levels, hierarchy)
    data = parser.parse_discourse('test_syllable_morpheme')
    return data
Ejemplo n.º 3
0
def subannotation_data():
    levels = [SegmentTier('label', 'phone'),
              OrthographyTier('label', 'word'),
              OrthographyTier('stop_information', 'phone')]
    levels[2].subannotation = True
    phones = [('k', 0.0, 0.1), ('ae', 0.1, 0.2), ('t', 0.2, 0.3), ('s', 0.3, 0.4),
              ('aa', 0.5, 0.6), ('r', 0.6, 0.7),
              ('k', 0.8, 0.9), ('u', 0.9, 1.0), ('t', 1.0, 1.1),
              ('d', 2.0, 2.1), ('aa', 2.1, 2.2), ('g', 2.2, 2.3), ('z', 2.3, 2.4),
              ('aa', 2.4, 2.5), ('r', 2.5, 2.6),
              ('t', 2.6, 2.7), ('uw', 2.7, 2.8),
              ('ay', 3.0, 3.1),
              ('g', 3.3, 3.4), ('eh', 3.4, 3.5), ('s', 3.5, 3.6)]
    words = [('cats', 0.0, 0.4), ('are', 0.5, 0.7), ('cute', 0.8, 1.1),
             ('dogs', 2.0, 2.4), ('are', 2.4, 2.6), ('too', 2.6, 2.8),
             ('i', 3.0, 3.1), ('guess', 3.3, 3.6)]
    info = [('burst', 0, 0.05), ('vot', 0.05, 0.1), ('closure', 0.2, 0.25),
            ('burst', 0.25, 0.26), ('vot', 0.26, 0.3), ('closure', 2.2, 2.25),
            ('burst', 2.25, 2.26), ('vot', 2.26, 2.3),
            ('voicing_during_closure', 2.2, 2.23), ('voicing_during_closure', 2.24, 2.25)]
    levels[0].add(phones)
    levels[1].add(words)
    levels[2].add(info)
    hierarchy = Hierarchy({'phone': 'word', 'word': None})
    parser = BaseParser(levels, hierarchy)
    data = parser.parse_discourse('test_sub')
    return data
Ejemplo n.º 4
0
def corpus_data_untimed():
    levels = [TextTranscriptionTier('transcription', 'word'),
              TextOrthographyTier('spelling', 'word'),
              TextMorphemeTier('morpheme', 'word'),
              GroupingTier('line', 'line')]

    transcriptions = [('k.ae.t-s', 0), ('aa.r', 1), ('k.y.uw.t', 2),
                      ('d.aa.g-z', 3), ('aa.r', 4), ('t.uw', 5),
                      ('ay', 6), ('g.eh.s', 7)]
    morphemes = [('cat-PL', 0), ('are', 1), ('cute', 2),
                 ('dog-PL', 3), ('are', 4), ('too', 5),
                 ('i', 6), ('guess', 7)]
    words = [('cats', 0), ('are', 1), ('cute', 2),
             ('dogs', 3), ('are', 4), ('too', 5),
             ('i', 6), ('guess', 7)]
    lines = [(0, 2), (3, 5), (6, 7)]

    levels[0].add(transcriptions)
    levels[1].add(words)
    levels[2].add(morphemes)
    levels[3].add(lines)

    hierarchy = Hierarchy({'word': 'line', 'line': None})
    parser = BaseParser(levels, hierarchy)
    data = parser.parse_discourse('test_untimed')
    return data
Ejemplo n.º 5
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def corpus_data_syllable_morpheme_srur():
    levels = [SegmentTier('sr', 'phone', label = True),
                TranscriptionTier('ur', 'word'),
                GroupingTier('syllable', 'syllable'),
                MorphemeTier('morphemes', 'word'),
                OrthographyTier('word', 'word'),
                GroupingTier('line', 'line')]

    srs = [('b', 0, 0.1), ('aa', 0.1, 0.2), ('k', 0.2, 0.3), ('s', 0.3, 0.4),
                ('ah', 0.4, 0.5), ('s', 0.5, 0.6),
            ('er', 0.7, 0.8),
            ('f', 0.9, 1.0), ('er', 1.0, 1.1),
            ('p', 1.2, 1.3), ('ae', 1.3, 1.4), ('k', 1.4, 1.5), ('eng', 1.5, 1.6)]
    urs = [('b.aa.k.s-ah.z', 0, 0.6), ('aa.r', 0.7, 0.8),
            ('f.ao.r', 0.9, 1.1), ('p.ae.k-ih.ng', 1.2, 1.6)]
    syllables = [(0, 0.3), (0.3, 0.6), (0.7, 0.8), (0.9, 1.1),
                (1.2, 1.5), (1.5, 1.6)]
    morphemes = [('box-PL', 0, 0.6), ('are', 0.7, 0.8),
                ('for', 0.9, 1.1), ('pack-PROG', 1.2, 1.6)]
    words = [('boxes', 0, 0.6), ('are', 0.7, 0.8),
            ('for', 0.9, 1.1), ('packing', 1.2, 1.6)]
    lines = [(0, 1.6)]

    levels[0].add(srs)
    levels[1].add(urs)
    levels[2].add(syllables)
    levels[3].add(morphemes)
    levels[4].add(words)
    levels[5].add(lines)

    hierarchy = Hierarchy({'phone': 'syllable', 'syllable': 'word',
                            'word': 'line', 'line': None})
    parser = BaseParser(levels, hierarchy)
    data = parser.parse_discourse('test_syllable_morpheme')
    return data
Ejemplo n.º 6
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def corpus_data_untimed():
    levels = [TextTranscriptionTier('transcription', 'word'),
                TextOrthographyTier('spelling', 'word'),
                TextMorphemeTier('morpheme', 'word'),
                GroupingTier('line', 'line')]

    transcriptions = [('k.ae.t-s', 0), ('aa.r', 1), ('k.y.uw.t', 2),
                    ('d.aa.g-z', 3), ('aa.r', 4), ('t.uw', 5),
                    ('ay', 6), ('g.eh.s', 7)]
    morphemes = [('cat-PL', 0), ('are', 1), ('cute', 2),
                ('dog-PL', 3), ('are', 4), ('too',5),
                ('i', 6), ('guess', 7)]
    words = [('cats', 0), ('are', 1), ('cute', 2),
            ('dogs', 3), ('are', 4), ('too', 5),
            ('i', 6), ('guess', 7)]
    lines = [(0, 2), (3, 5), (6, 7)]

    levels[0].add(transcriptions)
    levels[1].add(words)
    levels[2].add(morphemes)
    levels[3].add(lines)

    hierarchy = Hierarchy({'word': 'line', 'line': None})
    parser = BaseParser(levels, hierarchy)
    data = parser.parse_discourse('test_untimed')
    return data
Ejemplo n.º 7
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def corpus_data_ur_sr():
    levels = [SegmentTier('sr', 'phone'),
                OrthographyTier('word', 'word'),
                TranscriptionTier('ur', 'word')]
    srs = [('k', 0.0, 0.1), ('ae', 0.1, 0.2), ('s', 0.2, 0.4),
            ('aa', 0.5, 0.6), ('r', 0.6, 0.7),
            ('k', 0.8, 0.9), ('u', 0.9, 1.1),
            ('d',  2.0, 2.1), ('aa', 2.1, 2.2), ('g', 2.2, 2.25),
                ('ah', 2.25, 2.3), ('z', 2.3, 2.4),
            ('aa', 2.4, 2.5), ('r', 2.5, 2.6),
            ('t', 2.6, 2.7), ('uw', 2.7, 2.8),
            ('ay', 3.0, 3.1),
            ('g', 3.3, 3.4), ('eh', 3.4, 3.5), ('s', 3.5, 3.6)]
    words = [('cats', 0.0, 0.4), ('are', 0.5, 0.7), ('cute', 0.8, 1.1),
            ('dogs', 2.0, 2.4), ('are', 2.4, 2.6), ('too', 2.6, 2.8),
            ('i', 3.0, 3.1), ('guess', 3.3, 3.6)]
    urs = [('k.ae.t.s', 0.0, 0.4), ('aa.r', 0.5, 0.7), ('k.y.uw.t', 0.8, 1.1),
            ('d.aa.g.z', 2.0, 2.4), ('aa.r', 2.4, 2.6), ('t.uw', .6, 2.8),
            ('ay', 3.0, 3.1), ('g.eh.s', 3.3, 3.6)]
    levels[0].add(srs)
    levels[1].add(words)
    levels[2].add(urs)

    hierarchy = Hierarchy({'phone':'word', 'word': None})
    parser = BaseParser(levels, hierarchy)
    data = parser.parse_discourse('test_ursr')
    return data
Ejemplo n.º 8
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def corpus_data_timed():
    levels = [
        SegmentTier('label', 'phone'),
        OrthographyTier('label', 'word'),
        GroupingTier('line', 'line')
    ]
    phones = [('k', 0.0, 0.1), ('ae', 0.1, 0.2), ('t', 0.2, 0.3),
              ('s', 0.3, 0.4), ('aa', 0.5, 0.6), ('r', 0.6, 0.7),
              ('k', 0.8, 0.9), ('uw', 0.9, 1.0), ('t', 1.0, 1.1),
              ('d', 2.0, 2.1), ('aa', 2.1, 2.2), ('g', 2.2, 2.3),
              ('z', 2.3, 2.4), ('aa', 2.4, 2.5), ('r', 2.5, 2.6),
              ('t', 2.6, 2.7), ('uw', 2.7, 2.8), ('ay', 3.0, 3.1),
              ('g', 3.3, 3.4), ('eh', 3.4, 3.5), ('s', 3.5, 3.6)]
    words = [('cats', 0.0, 0.4), ('are', 0.5, 0.7), ('cute', 0.8, 1.1),
             ('dogs', 2.0, 2.4), ('are', 2.4, 2.6), ('too', 2.6, 2.8),
             ('i', 3.0, 3.1), ('guess', 3.3, 3.6)]
    lines = [(0.0, 1.1), (2.0, 2.8), (3.0, 3.6)]

    levels[0].add(phones)
    levels[1].add(words)
    levels[2].add(lines)
    hierarchy = Hierarchy({'phone': 'word', 'word': 'line', 'line': None})
    parser = BaseParser(levels, hierarchy)
    data = parser.parse_discourse('test_timed')
    return data
Ejemplo n.º 9
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def subannotation_data():
    levels = [SegmentTier('label', 'phone'),
                OrthographyTier('label', 'word'),
                OrthographyTier('stop_information', 'phone')]
    levels[2].subannotation = True
    phones = [('k', 0.0, 0.1), ('ae', 0.1, 0.2), ('t', 0.2, 0.3), ('s', 0.3, 0.4),
            ('aa', 0.5, 0.6), ('r',  0.6, 0.7),
            ('k', 0.8, 0.9), ('u', 0.9, 1.0), ('t', 1.0, 1.1),
            ('d', 2.0,  2.1), ('aa', 2.1, 2.2), ('g', 2.2, 2.3), ('z', 2.3, 2.4),
            ('aa', 2.4, 2.5), ('r', 2.5, 2.6),
            ('t', 2.6, 2.7), ('uw', 2.7, 2.8),
            ('ay', 3.0, 3.1),
            ('g', 3.3, 3.4), ('eh', 3.4, 3.5), ('s', 3.5, 3.6)]
    words = [('cats', 0.0, 0.4), ('are', 0.5, 0.7), ('cute', 0.8, 1.1),
            ('dogs', 2.0, 2.4), ('are', 2.4, 2.6), ('too', 2.6, 2.8),
            ('i', 3.0, 3.1), ('guess', 3.3, 3.6)]
    info = [('burst', 0, 0.05), ('vot', 0.05, 0.1), ('closure', 0.2, 0.25),
            ('burst', 0.25, 0.26), ('vot', 0.26, 0.3),('closure', 2.2, 2.25),
            ('burst', 2.25, 2.26), ('vot', 2.26, 2.3),
            ('voicing_during_closure', 2.2, 2.23),('voicing_during_closure', 2.24, 2.25)]
    levels[0].add(phones)
    levels[1].add(words)
    levels[2].add(info)
    hierarchy = Hierarchy({'phone':'word', 'word': None})
    parser = BaseParser(levels, hierarchy)
    data = parser.parse_discourse('test_sub')
    return data
Ejemplo n.º 10
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def corpus_data_untimed():
    levels = [
        TextTranscriptionTier("transcription", "word"),
        TextOrthographyTier("spelling", "word"),
        TextMorphemeTier("morpheme", "word"),
        GroupingTier("line", "line"),
    ]

    transcriptions = [
        ("k.ae.t-s", 0),
        ("aa.r", 1),
        ("k.y.uw.t", 2),
        ("d.aa.g-z", 3),
        ("aa.r", 4),
        ("t.uw", 5),
        ("ay", 6),
        ("g.eh.s", 7),
    ]
    morphemes = [("cat-PL", 0), ("are", 1), ("cute", 2), ("dog-PL", 3), ("are", 4), ("too", 5), ("i", 6), ("guess", 7)]
    words = [("cats", 0), ("are", 1), ("cute", 2), ("dogs", 3), ("are", 4), ("too", 5), ("i", 6), ("guess", 7)]
    lines = [(0, 2), (3, 5), (6, 7)]

    levels[0].add(transcriptions)
    levels[1].add(words)
    levels[2].add(morphemes)
    levels[3].add(lines)

    hierarchy = Hierarchy({"word": "line", "line": None})
    parser = BaseParser(levels, hierarchy)
    data = parser.parse_discourse("test_untimed")
    return data
Ejemplo n.º 11
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def subannotation_data():
    levels = [
        SegmentTier("label", "phone"),
        OrthographyTier("label", "word"),
        OrthographyTier("stop_information", "phone"),
    ]
    levels[2].subannotation = True
    phones = [
        ("k", 0.0, 0.1),
        ("ae", 0.1, 0.2),
        ("t", 0.2, 0.3),
        ("s", 0.3, 0.4),
        ("aa", 0.5, 0.6),
        ("r", 0.6, 0.7),
        ("k", 0.8, 0.9),
        ("u", 0.9, 1.0),
        ("t", 1.0, 1.1),
        ("d", 2.0, 2.1),
        ("aa", 2.1, 2.2),
        ("g", 2.2, 2.3),
        ("z", 2.3, 2.4),
        ("aa", 2.4, 2.5),
        ("r", 2.5, 2.6),
        ("t", 2.6, 2.7),
        ("uw", 2.7, 2.8),
        ("ay", 3.0, 3.1),
        ("g", 3.3, 3.4),
        ("eh", 3.4, 3.5),
        ("s", 3.5, 3.6),
    ]
    words = [
        ("cats", 0.0, 0.4),
        ("are", 0.5, 0.7),
        ("cute", 0.8, 1.1),
        ("dogs", 2.0, 2.4),
        ("are", 2.4, 2.6),
        ("too", 2.6, 2.8),
        ("i", 3.0, 3.1),
        ("guess", 3.3, 3.6),
    ]
    info = [
        ("burst", 0, 0.05),
        ("vot", 0.05, 0.1),
        ("closure", 0.2, 0.25),
        ("burst", 0.25, 0.26),
        ("vot", 0.26, 0.3),
        ("closure", 2.2, 2.25),
        ("burst", 2.25, 2.26),
        ("vot", 2.26, 2.3),
        ("voicing_during_closure", 2.2, 2.23),
        ("voicing_during_closure", 2.24, 2.25),
    ]
    levels[0].add(phones)
    levels[1].add(words)
    levels[2].add(info)
    hierarchy = Hierarchy({"phone": "word", "word": None})
    parser = BaseParser(levels, hierarchy)
    data = parser.parse_discourse("test_sub")
    return data
Ejemplo n.º 12
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def corpus_data_ur_sr():
    levels = [SegmentTier("sr", "phone"), OrthographyTier("word", "word"), TranscriptionTier("ur", "word")]
    srs = [
        ("k", 0.0, 0.1),
        ("ae", 0.1, 0.2),
        ("s", 0.2, 0.4),
        ("aa", 0.5, 0.6),
        ("r", 0.6, 0.7),
        ("k", 0.8, 0.9),
        ("u", 0.9, 1.1),
        ("d", 2.0, 2.1),
        ("aa", 2.1, 2.2),
        ("g", 2.2, 2.25),
        ("ah", 2.25, 2.3),
        ("z", 2.3, 2.4),
        ("aa", 2.4, 2.5),
        ("r", 2.5, 2.6),
        ("t", 2.6, 2.7),
        ("uw", 2.7, 2.8),
        ("ay", 3.0, 3.1),
        ("g", 3.3, 3.4),
        ("eh", 3.4, 3.5),
        ("s", 3.5, 3.6),
    ]
    words = [
        ("cats", 0.0, 0.4),
        ("are", 0.5, 0.7),
        ("cute", 0.8, 1.1),
        ("dogs", 2.0, 2.4),
        ("are", 2.4, 2.6),
        ("too", 2.6, 2.8),
        ("i", 3.0, 3.1),
        ("guess", 3.3, 3.6),
    ]
    urs = [
        ("k.ae.t.s", 0.0, 0.4),
        ("aa.r", 0.5, 0.7),
        ("k.y.uw.t", 0.8, 1.1),
        ("d.aa.g.z", 2.0, 2.4),
        ("aa.r", 2.4, 2.6),
        ("t.uw", 0.6, 2.8),
        ("ay", 3.0, 3.1),
        ("g.eh.s", 3.3, 3.6),
    ]
    levels[0].add(srs)
    levels[1].add(words)
    levels[2].add(urs)

    hierarchy = Hierarchy({"phone": "word", "word": None})
    parser = BaseParser(levels, hierarchy)
    data = parser.parse_discourse("test_ursr")
    return data
Ejemplo n.º 13
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def corpus_data_timed():
    levels = [SegmentTier("label", "phone"), OrthographyTier("label", "word"), GroupingTier("line", "line")]
    phones = [
        ("k", 0.0, 0.1),
        ("ae", 0.1, 0.2),
        ("t", 0.2, 0.3),
        ("s", 0.3, 0.4),
        ("aa", 0.5, 0.6),
        ("r", 0.6, 0.7),
        ("k", 0.8, 0.9),
        ("u", 0.9, 1.0),
        ("t", 1.0, 1.1),
        ("d", 2.0, 2.1),
        ("aa", 2.1, 2.2),
        ("g", 2.2, 2.3),
        ("z", 2.3, 2.4),
        ("aa", 2.4, 2.5),
        ("r", 2.5, 2.6),
        ("t", 2.6, 2.7),
        ("uw", 2.7, 2.8),
        ("ay", 3.0, 3.1),
        ("g", 3.3, 3.4),
        ("eh", 3.4, 3.5),
        ("s", 3.5, 3.6),
    ]
    words = [
        ("cats", 0.0, 0.4),
        ("are", 0.5, 0.7),
        ("cute", 0.8, 1.1),
        ("dogs", 2.0, 2.4),
        ("are", 2.4, 2.6),
        ("too", 2.6, 2.8),
        ("i", 3.0, 3.1),
        ("guess", 3.3, 3.6),
    ]
    lines = [(0.0, 1.1), (2.0, 2.8), (3.0, 3.6)]

    levels[0].add(phones)
    levels[1].add(words)
    levels[2].add(lines)
    hierarchy = Hierarchy({"phone": "word", "word": "line", "line": None})
    parser = BaseParser(levels, hierarchy)
    data = parser.parse_discourse("test_timed")
    return data
Ejemplo n.º 14
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def corpus_data_syllable_morpheme_srur():
    levels = [
        SegmentTier("sr", "phone"),
        TranscriptionTier("ur", "word"),
        GroupingTier("syllable", "syllable"),
        MorphemeTier("morphemes", "word"),
        OrthographyTier("word", "word"),
        GroupingTier("line", "line"),
    ]

    srs = [
        ("b", 0, 0.1),
        ("aa", 0.1, 0.2),
        ("k", 0.2, 0.3),
        ("s", 0.3, 0.4),
        ("ah", 0.4, 0.5),
        ("s", 0.5, 0.6),
        ("er", 0.7, 0.8),
        ("f", 0.9, 1.0),
        ("er", 1.0, 1.1),
        ("p", 1.2, 1.3),
        ("ae", 1.3, 1.4),
        ("k", 1.4, 1.5),
        ("eng", 1.5, 1.6),
    ]
    urs = [("b.aa.k.s-ah.z", 0, 0.6), ("aa.r", 0.7, 0.8), ("f.ao.r", 0.9, 1.1), ("p.ae.k-ih.ng", 1.2, 1.6)]
    syllables = [(0, 0.3), (0.3, 0.6), (0.7, 0.8), (0.9, 1.1), (1.2, 1.5), (1.5, 1.6)]
    morphemes = [("box-PL", 0, 0.6), ("are", 0.7, 0.8), ("for", 0.9, 1.1), ("pack-PROG", 1.2, 1.6)]
    words = [("boxes", 0, 0.6), ("are", 0.7, 0.8), ("for", 0.9, 1.1), ("packing", 1.2, 1.6)]
    lines = [(0, 1.6)]

    levels[0].add(srs)
    levels[1].add(urs)
    levels[2].add(syllables)
    levels[3].add(morphemes)
    levels[4].add(words)
    levels[5].add(lines)

    hierarchy = Hierarchy({"phone": "syllable", "syllable": "word", "word": "line", "line": None})
    parser = BaseParser(levels, hierarchy)
    data = parser.parse_discourse("test_syllable_morpheme")
    return data
Ejemplo n.º 15
0
def corpus_data_timed():
    levels = [SegmentTier('label', 'phone'),
                OrthographyTier('label', 'word'),
                GroupingTier('line', 'line')]
    phones = [('k', 0.0, 0.1), ('ae', 0.1, 0.2), ('t', 0.2, 0.3), ('s', 0.3, 0.4),
            ('aa', 0.5, 0.6), ('r',  0.6, 0.7),
            ('k', 0.8, 0.9), ('uw', 0.9, 1.0), ('t', 1.0, 1.1),
            ('d', 2.0,  2.1), ('aa', 2.1, 2.2), ('g', 2.2, 2.3), ('z', 2.3, 2.4),
            ('aa', 2.4, 2.5), ('r', 2.5, 2.6),
            ('t', 2.6, 2.7), ('uw', 2.7, 2.8),
            ('ay', 3.0, 3.1),
            ('g', 3.3, 3.4), ('eh', 3.4, 3.5), ('s', 3.5, 3.6)]
    words = [('cats', 0.0, 0.4), ('are', 0.5, 0.7), ('cute', 0.8, 1.1),
            ('dogs', 2.0, 2.4), ('are', 2.4, 2.6), ('too', 2.6, 2.8),
            ('i', 3.0, 3.1), ('guess', 3.3, 3.6)]
    lines = [(0.0, 1.1), (2.0, 2.8), (3.0, 3.6)]

    levels[0].add(phones)
    levels[1].add(words)
    levels[2].add(lines)
    hierarchy = Hierarchy({'phone':'word', 'word': 'line', 'line': None})
    parser = BaseParser(levels, hierarchy)
    data = parser.parse_discourse('test_timed')
    return data