Table 3 New training/development queries used in the 2014 evaluation and not in the 2012 evaluation, time length per query (in milliseconds), and number of occurrences per query
From: Comparison of ALBAYZIN query-by-example spoken term detection 2012 and 2014 evaluations
Query (time)–(# occ.) | Query (time)–(# occ.) |
|---|---|
Presentación (760)–(17) | Portugal (340)–(4) |
Vosotros (360)–(6) | Parlamento (360)–(3) |
Etcétera (490)–(28) | Microsoft (580)–(4) |
Empresas (820)–(71) | Mavir (420)–(2) |
Porcentaje (490)–(6) | Málaga (450)–(2) |
Experimentos (400)–(10) | Isabel (310)–(4) |
Noventa (630)–(39) | Garner (320)–(3) |
Atención (280)–(8) | Galicia (520)–(4) |
Mercado (510)–(111) | Erasmus (430)–(2) |
Resolver (500)–(8) | Dilbert (640)–(2) |
Probablemente (490)–(6) | Complutense (460)–(4) |
Dominios (370)–(17) | Cristian (510)–(2) |
Wikipedia (670)–(3) | Berrilan (430)–(2) |
Webmaster (460)–(2) | Aguilera (480)–(3) |
Valladolid (530)–(2) | Premios nobel (650)–(2) |
Sevilla (450)–(2) | Universidad de Chile (840)–(3) |
Profit (330)–(3) | Nick cohn (410)–(3) |