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📄 wlat-format.5

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wlat-format(5)                                     wlat-format(5)NNAAMMEE       wlat-format  -  File  format for SRILM word posterior lat-       ticesSSYYNNOOPPSSIISS       Word lattices:       vveerrssiioonn 22       nnaammee _s       iinniittiiaall _i       ffiinnaall _f       nnooddee _n _w _a _p _n_1 _p_1 _n_2 _p_2 ...       ...       Word meshes (confusion networks):       nnaammee _s       nnuummaalliiggnnss _N       ppoosstteerriioorr _P       aalliiggnn _a _w_1 _p_1 _w_2 _p_2 ...       rreeffeerreennccee _a _w       hhyyppss _a _w _h_1 _h_2 ...       iinnffoo _a _w _s_t_a_r_t _d_u_r _a_s_c_o_r_e _g_s_c_o_r_e _p_h_o_n_e_s _p_h_o_n_e_d_u_r_s       ...DDEESSCCRRIIPPTTIIOONN       Word posterior lattices and meshes are lattices  generated       by aligning N-best hypotheses with nnbbeesstt--llaattttiiccee(1), or by       aligning PFSG or HTK lattices with llaattttiiccee--ttooooll(1).   They       compactly  encode  possible  word hypotheses sequences and       their posterior probabilities.  (Word meshes  have  become       generally    known    as    ``confusion    networks''   or       ``sausages.'')       A word lattice is a partially ordered directed graph  with       nodes  representing word hypotheses.  Nodes are identified       by non-negative integers.  The file format  specifies  the       initial  node _i, the final node _f, and any number of addi-       tional nodes _n.  For each node _n the following  associated       information is given on the same line: the word identity _w       (the string  ``NULL''  is  used  with  initial  and  final       nodes), the alignment position _a (identical values in this       field identify hypotheses that occur  at  the  same  posi-       tion),  and  the  word posterior probability _p.  Following       these values, zero or more transitions to successor  nodes       are  specified,  each  given  by the node index _n_i and the       transition posterior probability _p_i.  In a  properly  nor-       malized  word  lattice the transition posteriors _p_i sum up       to the node posterior _p.       Word meshes represent a more constrained lattice format in       which  word  hypotheses are in a total order.  A mesh con-       tains a number of alignment positions, and a set of  mutu-       ally  exclusive  word  hypotheses  in  each  position (the       ``confusion sets'').  The word mesh  represents  all  sen-       tence hypotheses that can be generated by freely combining       word hypotheses at each position.  The file format  speci-       fies  the  number  of  alignment positions _A and the total       posterior probability mass _P  contained  in  the  lattice,       followed by one or more confusion set specifications.  For       each alignment position _a, the hypothesized words  _w_i  and       their  posterior  probabilities  _p_i are listed in alterna-       tion.  The pseudo-word string **DDEELLEETTEE** represents an empty       hypothesis.       Optionally, the word mesh format encodes additional infor-       mation  about  the  hypothesis  alignment  from  which  it       resulted.   The  keyword  rreeffeerreennccee  specifies the correct       word _w that was aligned at position _a.  The  keyword  hhyyppss       is used to list the sentence hypotheses of which a certain       word hypothesis was a part.  The word hypothesis is  iden-       tified  by  an  alignment postion _a and the word string _w,       and is followed by the integer IDs _h_i (typically,  the  N-       best ranks) of the associated sentence hypotheses.       As  another  optional  element,  the word mesh can contain       word-level acoustic and  temporal  information,  following       the  keyword  iinnffoo, the alignment position _a, and the word       identity _w.  This information  is  derived  by  nnbbeesstt--llaatt--       ttiiccee(1)  from  word-  and phone-level backtraces of N-best       hypotheses (as represented in Decipher  NBestList2.0  for-       mat).   The details of this information are defined in the       SRILM class NNBBeessttWWoorrddIInnffoo and subject to change, but  cur-       rently  include the following.  _s_t_a_r_t: word start time (in       seconds from the beginning of  the  waveform);  _d_u_r:  word       duration  (in  seconds); _a_s_c_o_r_e: acoustic model likelihood       (log base 10);  _g_s_c_o_r_e:  grammar  (LM  and  pronunciation)       score  (log  base  10); _p_h_o_n_e_s: sequence of phones in word       (separated by colons); _p_h_o_n_e_d_u_r_s: sequence of phone  dura-       tions  (in  numbers of frames, separated by colons).  When       word meshes are derived from HTK format lattices,  pronun-       ciation  field  will  consist  of  the HTK phone alignment       information, which encodes both phone sequence  and  dura-       tions;  the phone duration field in turn is used to encode       the duration model scores, if present.  NNoottee:: The  encoded       information pertains to the word hypothesis with the high-       est per-unit-time acoustic score among all  hypotheses  of       the same word aligned to a given word mesh position.       Both  formats  optionally  encode the associated utterance       IDs in the nnaammee field.  Word lattices and  meshes  can  be       converted to PFSG format using the script wwllaatt--ttoo--ppffssgg.SSEEEE AALLSSOO       nbest-lattice(1),  lattice-tool(1), pfsg-scripts(1), pfsg-       format(5), nbest-format(5).       L. Mangu, E. Brill, & A. Stolcke, ``Finding  consensus  in       speech  recognition:  word  error  minimization  and other       applications of confusion networks,'' _C_o_m_p_u_t_e_r _S_p_e_e_c_h  _a_n_d       _L_a_n_g_u_a_g_e 14(4), 373-400, 2000.BBUUGGSS       Detailed alignment and acoustic information is so far only       implemented for  word  meshes,  although  conceptually  it       would apply equally to word lattices.AAUUTTHHOORR       Andreas Stolcke <stolcke@speech.sri.com>.       Copyright 2001-2005 SRI InternationalSRILM File Formats $Date: 2005/08/22 19:14:08 $    wlat-format(5)

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