{"id":"https://openalex.org/W2899459239","doi":"https://doi.org/10.18653/v1/k18-1043","title":"","display_name":"","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2899459239","doi":"https://doi.org/10.18653/v1/k18-1043","mag":"2899459239"},"language":null,"primary_location":{"id":"doi:10.18653/v1/k18-1043","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/k18-1043","pdf_url":"https://www.aclweb.org/anthology/K18-1043.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd Conference on Computational Natural Language Learning","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/K18-1043.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100771485","display_name":"Min Li","orcid":"https://orcid.org/0000-0001-5428-6276"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Min Li","raw_affiliation_strings":["IBM Research"],"affiliations":[{"raw_affiliation_string":"IBM Research","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048281388","display_name":"Marina Danilevsky","orcid":"https://orcid.org/0000-0003-2875-2442"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marina Danilevsky","raw_affiliation_strings":["IBM Research"],"affiliations":[{"raw_affiliation_string":"IBM Research","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033381387","display_name":"Sara Noeman","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sara Noeman","raw_affiliation_strings":["IBM Research"],"affiliations":[{"raw_affiliation_string":"IBM Research","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102944075","display_name":"Yunyao Li","orcid":"https://orcid.org/0009-0002-0814-4634"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yunyao Li","raw_affiliation_strings":["IBM Research"],"affiliations":[{"raw_affiliation_string":"IBM Research","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100771485"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6515,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.77326138,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"444","last_page":"453"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9894999861717224,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pinyin","display_name":"Pinyin","score":0.8601701855659485},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8109521865844727},{"id":"https://openalex.org/keywords/pronunciation","display_name":"Pronunciation","score":0.7875401973724365},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6531331539154053},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5947909951210022},{"id":"https://openalex.org/keywords/reciprocal","display_name":"Reciprocal","score":0.5886676907539368},{"id":"https://openalex.org/keywords/mean-reciprocal-rank","display_name":"Mean reciprocal rank","score":0.5797810554504395},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5788520574569702},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5024712085723877},{"id":"https://openalex.org/keywords/tone","display_name":"Tone (literature)","score":0.43789204955101013},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.41760244965553284},{"id":"https://openalex.org/keywords/chinese-characters","display_name":"Chinese characters","score":0.2131626009941101},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.19727963209152222},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10416397452354431},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.0728987455368042}],"concepts":[{"id":"https://openalex.org/C2781095461","wikidata":"https://www.wikidata.org/wiki/Q42222","display_name":"Pinyin","level":3,"score":0.8601701855659485},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8109521865844727},{"id":"https://openalex.org/C2780844864","wikidata":"https://www.wikidata.org/wiki/Q184377","display_name":"Pronunciation","level":2,"score":0.7875401973724365},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6531331539154053},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5947909951210022},{"id":"https://openalex.org/C2777742833","wikidata":"https://www.wikidata.org/wiki/Q1964083","display_name":"Reciprocal","level":2,"score":0.5886676907539368},{"id":"https://openalex.org/C44083865","wikidata":"https://www.wikidata.org/wiki/Q3853443","display_name":"Mean reciprocal rank","level":2,"score":0.5797810554504395},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5788520574569702},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5024712085723877},{"id":"https://openalex.org/C2780583480","wikidata":"https://www.wikidata.org/wiki/Q1366327","display_name":"Tone (literature)","level":2,"score":0.43789204955101013},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.41760244965553284},{"id":"https://openalex.org/C2781051154","wikidata":"https://www.wikidata.org/wiki/Q8201","display_name":"Chinese characters","level":2,"score":0.2131626009941101},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.19727963209152222},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10416397452354431},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0728987455368042},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/k18-1043","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/k18-1043","pdf_url":"https://www.aclweb.org/anthology/K18-1043.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd Conference on Computational Natural Language Learning","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/k18-1043","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/k18-1043","pdf_url":"https://www.aclweb.org/anthology/K18-1043.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd Conference on Computational Natural Language Learning","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.7699999809265137,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2899459239.pdf","grobid_xml":"https://content.openalex.org/works/W2899459239.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W157541337","https://openalex.org/W1506507878","https://openalex.org/W1520449809","https://openalex.org/W1965545650","https://openalex.org/W1966758174","https://openalex.org/W2001496424","https://openalex.org/W2006426911","https://openalex.org/W2030019187","https://openalex.org/W2053705431","https://openalex.org/W2061504941","https://openalex.org/W2086511124","https://openalex.org/W2107038463","https://openalex.org/W2144226312","https://openalex.org/W2147686939","https://openalex.org/W2149498186","https://openalex.org/W2149623920","https://openalex.org/W2151941172","https://openalex.org/W2170353620","https://openalex.org/W2203357322","https://openalex.org/W2250297702","https://openalex.org/W2251404146","https://openalex.org/W2355285064","https://openalex.org/W2548759296","https://openalex.org/W2962699518","https://openalex.org/W2999282340","https://openalex.org/W4285719527","https://openalex.org/W4300869073"],"related_works":["https://openalex.org/W2887783441","https://openalex.org/W2185608395","https://openalex.org/W596678143","https://openalex.org/W2032265864","https://openalex.org/W2902315172","https://openalex.org/W2382908608","https://openalex.org/W2186284405","https://openalex.org/W170359345","https://openalex.org/W2112572610","https://openalex.org/W1973552820"],"abstract_inverted_index":{"Phonetic":[0],"similarity":[1,48,98],"algorithms":[2],"identify":[3],"words":[4],"and":[5,28,64,83],"phrases":[6],"with":[7],"similar":[8],"pronunciation":[9],"which":[10],"are":[11,22,55,73],"used":[12],"in":[13],"many":[14],"natural":[15],"language":[16],"processing":[17],"tasks.":[18],"However,":[19],"existing":[20],"approaches":[21],"designed":[23],"mainly":[24],"for":[25,50],"Indo-European":[26],"languages":[27],"fail":[29],"to":[30,60],"capture":[31],"the":[32,78,95],"unique":[33],"properties":[34],"of":[35,80],"Chinese":[36],"pronunciation.":[37],"In":[38],"this":[39],"paper,":[40],"we":[41],"propose":[42],"a":[43,87],"high":[44],"dimensional":[45],"encoded":[46],"phonetic":[47,71,97],"algorithm":[49],"Chinese,":[51],"DIMSIM.":[52],"The":[53],"encodings":[54],"learned":[56],"from":[57],"annotated":[58],"data":[59],"separately":[61],"map":[62],"initial":[63],"final":[65,82],"phonemes":[66],"into":[67],"n-dimensional":[68],"coordinates.":[69],"Pinyin":[70],"similarities":[72,79],"then":[74],"calculated":[75],"by":[76],"aggregating":[77],"initial,":[81],"tone.":[84],"DIMSIM":[85],"demonstrates":[86],"7.5X":[88],"improvement":[89],"on":[90],"mean":[91],"reciprocal":[92],"rank":[93],"over":[94],"state-of-theart":[96],"approaches.":[99]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2018-11-09T00:00:00"}
