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The dataset generation failed because of a cast error
Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 2 new columns ({'aachen', 'ˈɑkən'}) and 2 missing columns ({'2-Butins', 'ˌt͡svaɪ̯buˈtiːns'}).

This happened while the csv dataset builder was generating data using

hf://datasets/crane-local-ai/test-data/g2p/en_us/test.tsv (at revision 19b6ea610af45d9258a3957c7a22694280bdf145), ['hf://datasets/crane-local-ai/test-data@19b6ea610af45d9258a3957c7a22694280bdf145/g2p/de_de/test.tsv', 'hf://datasets/crane-local-ai/test-data@19b6ea610af45d9258a3957c7a22694280bdf145/g2p/en_us/test.tsv']

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1837, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 765, in write_table
                  self._write_table(pa_table, writer_batch_size=writer_batch_size)
                  ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              aachen: string
              ˈɑkən: string
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 532
              to
              {'2-Butins': Value('string'), 'ˌt͡svaɪ̯buˈtiːns': Value('string')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1683, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1839, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
                  ...<4 lines>...
                  )
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 2 new columns ({'aachen', 'ˈɑkən'}) and 2 missing columns ({'2-Butins', 'ˌt͡svaɪ̯buˈtiːns'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/crane-local-ai/test-data/g2p/en_us/test.tsv (at revision 19b6ea610af45d9258a3957c7a22694280bdf145), ['hf://datasets/crane-local-ai/test-data@19b6ea610af45d9258a3957c7a22694280bdf145/g2p/de_de/test.tsv', 'hf://datasets/crane-local-ai/test-data@19b6ea610af45d9258a3957c7a22694280bdf145/g2p/en_us/test.tsv']
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

2-Butins
string
ˌt͡svaɪ̯buˈtiːns
string
3-wöchigen
ˈdʁaɪ̯ˌvœçɪɡn̩
50-Franken-Noten
fʏnft͡sɪçˈfʁaŋkn̩ˌnoːtn̩
50ern
fʏnft͡sɪɡɐn
Aalfett
ˈaːlˌfɛt
Aalmolchen
ˈaːlˌmɔlçn̩
Aase
ˈaːzə
Abadie-Zeichens
abaˈdiːˌt͡saɪ̯çn̩s
Abbildungsmaßstabe
ˈapbɪldʊŋsˌmaːsʃtaːbə
Abbildungsmaßstabs
ˈapbɪldʊŋsˌmaːsʃtaːps
Abendblätter
ˈaːbn̩tˌblɛtɐ
Abiologie
ˌabi̯oloˈɡiː
Abkürzungsverzeichnissen
ˈapkʏʁt͡sʊŋsfɛɐ̯ˌt͡saɪ̯çnɪsn̩
Abrüstungen
ˈapʁʏstʊŋən
Abschiedes
ˈapˌʃiːdəs
Abschiedsessens
ˈapʃiːt͡sˌʔɛsn̩s
Abwasserkanälen
ˈapvasɐkaˌnɛːlən
Abwehrkraft
ˈapveːɐ̯ˌkʁaft
Abänderungsvorschlage
ˈapʔɛndəʁʊŋsˌfoːɐ̯ʃlaːɡə
Acetatpuffers
at͡səˈtaːtˌpʊfɐs
Ach-Lauts
axˌlaʊ̯t͡s
Achselhöhlen
ˈaksəlˌhøːlən
Acht-Stunden-Tags
axtˈʃtʊndn̩ˌtaːks
Acrylaten
akʁyˈlaːtn̩
Adaldagen
ˈaːdalˌdaːɡən
Adalmanns
ˈaːdalˌmans
Adelbrande
ˈaːdl̩bʁandə
Adelmunde
ˈaːdl̩mʊndə
Adygeischen
adyˈɡeːɪʃn̩
Affixoides
afɪksoˈiːdəs
Afrikakenners
ˈafʁikaˌkɛnɐs
Akia
ˈakja
Aktenordners
ˈaktn̩ˌʔɔʁdnɐs
Aktmalerei
aktmaːləˈʁaɪ̯
Alberichen
ˈalbəʁɪçn̩
Aldebert
ˈaldəbɛʁt
Alizarin
alit͡saˈʁiːn
Alleinspielers
aˈlaɪ̯nˌʃpiːlɐs
Allgemeinarzt
ˈalɡəˈmaɪ̯nˌʔaʁt͡st
Alligatorsalamandern
aliˈɡaːtoːɐ̯zalaˌmandɐn
Allwissenheit
alˈvɪsn̩haɪ̯t
Alsleben
ˈalsˌleːbn̩
Altenglischs
ˈaltˌʔɛŋlɪʃs
Altistinnen
alˈtɪstɪnən
Amazonasbewohner
amaˈt͡soːnasbəˌvoːnɐ
Amazonenstromes
amaˈt͡soːnənˌʃtʁoːməs
Ameisenigels
ˈaːmaɪ̯zn̩ˌʔiːɡl̩s
Amperemetern
ampeːɐ̯ˈmeːtɐn
Amphimacer
amˈfiːmat͡sɐ
Amphimacern
amˈfiːmat͡sɐn
Amphimazers
amˈfiːmat͡sɐs
Amrita
amˈʁɪta
Amtshandlung
ˈamt͡sˌhandlʊŋ
Amuletten
amuˈlɛtn̩
Anarchosyndikalist
aˌnaʁçozʏndikaˈlɪst
Andreaskreuz
anˈdʁeːasˌkʁɔɪ̯t͡s
Anetamin
anetaˈmiːn
Anfahrtswegs
ˈanfaːɐ̯t͡sˌveːks
Angeklagtem
ˈanɡəˌklaːktəm
Angeltouren
ˈaŋl̩ˌtuːʁən
Ankreis
ˈanˌkʁaɪ̯s
Anschauungskräfte
ˈanʃaʊ̯ʊŋsˌkʁɛftə
Anschlage
ˈanˌʃlaːɡə
Anstaltspersonal
ˈanʃtalt͡spɛʁzoˌnaːl
Anti-Terror-Mission
antiˈtɛʁoːɐ̯mɪˌsi̯oːn
Antiarrhythmikum
ˌantiʔaˈʁʏtmikʊm
Antihistaminikums
antihɪstaˈmiːnikʊms
Antikommunist
ˈantikɔmuˌnɪst
Anwohnerparkausweises
ˈanvoːnɐˌpaʁkʔaʊ̯svaɪ̯zəs
Anzugs
ˈant͡suːks
Apfelkerne
ˈap͡fl̩ˌkɛʁnə
Apfelkorne
ˈap͡fl̩ˌkɔʁnə
Apnoetauchern
aˈpnoːəˌtaʊ̯xɐn
Aquarellmalerin
akvaˈʁɛlˌmaːləʁɪn
Arbeitsalltags
ˈaʁbaɪ̯t͡sˌʔaltaːks
Arbeitsministers
ˈaʁbaɪ̯t͡smiˌnɪstɐs
Archons
ˈaʁçɔns
Archäometrie
aʁçɛomeˈtʁiː
Ariernachweis
ˈaːʁiɐˌnaːxvaɪ̯s
Aromunen
aʁoˈmuːnən
Arosas
aˈʁoːzaːs
Artikulationsorgan
aʁtikulaˈt͡si̯oːnsʔɔʁˌɡaːn
Artillerien
ˈaʁtɪləʁiːən
Aschaffenburgs
aˈʃafn̩ˌbʊʁks
Aschenputtels
ˈaʃn̩pʊtl̩s
Assemblagen
asɑ̃ˈblaːʒn̩
Assistenzärzte
asɪsˈtɛnt͡sˌʔɛʁt͡stə
Astronomischen Kalender
astʁoˌnoːmɪʃn̩ kaˈlɛndɐ
Atomabkommen
aˈtoːmʔapˌkɔmən
Atomkerne
aˈtoːmˌkɛʁnə
Atomphysiker
aˈtoːmˌfyːzɪkɐ
Auffassungen
ˈaʊ̯fˌfasʊŋən
Aufpasserinnen
ˈaʊ̯fˌpasəʁɪnən
Aufriss
ˈaʊ̯fˌʁɪs
Augsburg
ˈaʊ̯ksbʊʁk
Augäpfeln
ˈaʊ̯kˌʔɛp͡fl̩n
Ausdruck
ˈaʊ̯sˌdʁʊk
Ausdrucksmittels
ˈaʊ̯sdʁʊksˌmɪtl̩s
Auslandseinsatz
ˈaʊ̯slant͡sˌʔaɪ̯nzat͡s
Auslandsinvestition
ˈaʊ̯slant͡sʔɪnvɛstiˌt͡si̯oːn
Auswanderungswelle
ˈaʊ̯svandəʁʊŋsˌvɛlə
End of preview.

G2P Test Fixtures

Held-out word-to-IPA test sets for evaluating grapheme-to-phoneme accuracy, used by Crane's test suite and benchmarks. These are static test fixtures, not runtime model assets.

Files

File Language Entries Description
g2p/en_us/test.tsv English (US) 5000 Held-out word-IPA pairs for CER benchmarking
g2p/de_de/test.tsv German 5000 Held-out word-IPA pairs for CER benchmarking
g2p/kokoro_vocab.json n/a 114 Kokoro phoneme vocabulary (char → token ID) used by the normalizer correctness benchmark
g2p/en_us/kokoro_normalizer_ref.tsv English (US) 71 Raw IPA → expected (en_us, Kokoro) normalized IPA + phoneme IDs, for IpaNormalizer regression testing
g2p/de_de/kokoro_normalizer_ref.tsv German 32 Raw IPA → expected (de, Kokoro) normalized IPA + phoneme IDs, for IpaNormalizer regression testing

Format

g2p/en_us/test.tsv and g2p/de_de/test.tsv: tab-separated, two columns, UTF-8, no header row, sorted alphabetically:

word<TAB>IPA

Example:

abandons	əbˈændənz

g2p/en_us/kokoro_normalizer_ref.tsv and g2p/de_de/kokoro_normalizer_ref.tsv: tab-separated, three columns, UTF-8, no header row:

raw_ipa<TAB>expected_normalized_ipa<TAB>expected_phoneme_ids

expected_phoneme_ids is a comma-separated list of i64 token IDs, with a 0 (pad/BOS) prepended and appended, matching Moonshine's phoneme_str_to_input_ids(). Example:

tˈiːtʃɚ	tˈiːʧəɹ	0,62,156,51,158,133,83,123,0

g2p/kokoro_vocab.json: a flat JSON object mapping each phoneme character to its integer token ID, e.g. {"a": 43, "ˈ": 156, ...}.

Provenance

g2p/en_us/test.tsv is a 5000-entry random sample (seed 42, no replacement) from Moonshine Voice's (https://github.com/moonshine-ai/moonshine, MIT license) English IPA lexicon, which is itself derived from the CMU Pronouncing Dictionary (https://github.com/cmusphinx/cmudict, BSD-style license). These entries are held out and never seen by the G2P engine during lexicon construction.

g2p/de_de/test.tsv is a 5000-entry random sample (seed 42, no replacement, one pronunciation per word) from Moonshine Voice's German IPA lexicon (MIT-licensed multilingual IPA dictionary data), deduplicated to unique words before sampling since the source lexicon has multiple pronunciation rows for some words. These entries are held out and never seen by the G2P engine during lexicon construction.

g2p/kokoro_vocab.json is copied verbatim from Moonshine Voice's core/moonshine-tts/data/kokoro/config.json vocab object (114 entries; the HuggingFace onnx-community/Kokoro-82M-v1.0-ONNX export used by Crane's kokoro_tts module has the same 114 entries plus one extra, $, which does not affect this normalizer's behavior).

g2p/en_us/kokoro_normalizer_ref.tsv combines the first 50 lines of Moonshine's own golden English G2P output (core/moonshine-tts/tests/data/en_us/rule_g2p_wiki_100.txt) with 21 hand-crafted edge cases (empty/whitespace-only input, each of the 12 diphthong/affricate/rhotic replacements in isolation, unknown-codepoint dropping, non-ASCII whitespace collapsing). Expected output was generated by an independent Python reimplementation of Moonshine's normalize_ipa_to_kokoro() and phoneme_str_to_input_ids() (moonshine-tts.cpp), not by running the C++ itself — the 12 replacement pairs and the vocab-filter/whitespace-collapse logic are simple enough that this port only needs str.replace, str.strip, and Python's unicodedata.normalize("NFC", ...).

g2p/de_de/kokoro_normalizer_ref.tsv combines 6 realistic German lexicon entries sampled from g2p/de_de/test.tsv (single words plus one 2-word combination, chosen to exercise both plain lexicon passthrough and the affricate/geminate/ʏ replacements together with dropped combining diacritics) with 26 hand-crafted edge cases (each DE_EXTRA_KOKORO_REPLACEMENTS pair in isolation, shared affricate/diphthong passthrough under "de", German phonemes with no replacement needed, syllabic-consonant and non-syllabic-offglide diacritic dropping, unknown-codepoint dropping, and whitespace handling). Expected output was hand-derived by applying SHARED_KOKORO_REPLACEMENTS/DE_EXTRA_KOKORO_REPLACEMENTS and the vocab-filter/whitespace-collapse algorithm against g2p/kokoro_vocab.json directly, then cross-checked by running the real IpaNormalizer and confirming an exact match — not authored by trusting normalize()'s own output as ground truth.

License

Both upstream sources use permissive, MIT-compatible licenses:

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