In order to build a set of HMMs, a set of speech data files and their associated transcriptions are required. Very often speech data will be obtained from database archives, typically on CD-ROMs. Before it can be used in training, it must be converted into the appropriate parametric form and any associated transcriptions must be converted to have the correct format and use the required phone or word labels. If the speech needs to be recorded, then the tool HSLAB can be used both to record the speech and to manually annotate it with any required transcriptions.
Although all HTK tools can parameterise waveforms on-the-fly, in practice it is usually better to parameterise the data just once. The tool HCOPY is used for this. As the name suggests, HCOPY is used to copy one or more source files to an output file. Normally, HCOPY copies the whole file, but a variety of mechanisms are provided for extracting segments of files and concatenating files. By setting the appropriate configuration variables, all input files can be converted to parametric form as they are read-in. Thus, simply copying each file in this manner performs the required encoding. The tool HLIST can be used to check the contents of any speech file and since it can also convert input on-the-fly, it can be used to check the results of any conversions before processing large quantities of data. Transcriptions will also need preparing. Typically the labels used in the original source transcriptions will not be exactly as required, for example, because of differences in the phone sets used. Also, HMM training might require the labels to be context-dependent. The tool HLED is a script-driven label editor which is designed to make the required transformations to label files. HLED can also output files to a single Master Label File MLF which is usually more convenient for subsequent processing. Finally on data preparation, HLSTATS can gather and display statistics on label files and where required, HQUANT can be used to build a VQ codebook in preparation for building discrete probability HMM system.