# Experimenting the Automatic Recognition of Non-Conventionalized Units in Sign Language
## 2 Materials and Methods
### Better Corpora for Continuous Sign Language Recognition  
#### 2.1.1 A Few Corpora Made by Linguists  
Conversely to SIGNUM, RWTH-PW and CSLR100, many SL corpora have been made by linguists. We introduce six of them: the Auslan Corpus [7], the BSL Corpus (BSLCP) [38], the DGS Korpus [39], the LSFB Corpus [40], the NCSLGR corpus [41] and Corpus NGT [42; 43]. An overview of these corpora, along with those presented in Section 1.2.1, is given in Table 2. In this table, we include the number of signers, total duration, discourse type, and whether a written translation is included in the annotation as well as the annotation categories (besides lexical sign glosses).  
Except for NCSLGR, these corpora are large in terms of duration, they include many signers and are made of dialogues, narratives and conversations. Undoubtedly, they can be considered very representative of natural SL. These corpora contain very interesting annotation information outside lexicon: PTSs for the Auslan Corpus, BSLCP and NCSLGR; DSs for the Auslan Corpus, BSLCP, the LSFB Corpus, Corpus NGT and NCSLGR; Constructed action for the Auslan Corpus; FBuoys for BSLCP; Mouthing for the DGS Korpus and Corpus NGT; FSs for NCSLGR. However, because these corpora have been made by linguists and intended for linguistic analysis, using them for SLR tasks is not straightforward. The main reason for this is the lack of consistency in the annotations across the corpora: most of them are still ongoing work, with annotations being updated continuously.  
\begin{table}
\begin{tabular}{l c c c c c c} \hline \hline
**Corpus (SL)** & **Signers** & **Hrs.** & \
\begin{tabular}{c} **Discourse** \\ **Type** \\ \end{tabular} & **Translation** &
\begin{tabular}{c} **Annotation Outside Lexicon** \\ **Categories** \\ \end{tabular} & **Used for** \\ \hline
[15] CSLR100 (ChSL) & 50 & 100 & Artificial & - & - & SLR \\
[11] RWTH-PW (DGS) & 9 & 11 & Interpreted & German & - & SLR \\
[10] SIGNUM (DGS) & 25 & 5 & Artificial & Ger./Eng. & - & SLR \\ \hline
[41] NCSLGR (ASL) & 7 & 2 & Mixed & - & PTSs, DSs, FSs & Yes &
\begin{tabular}{c} SLR \& \\ linguistics \\ \end{tabular} \\
[7] Auslan Corpus & 100 & 150 & Natural & - &
\begin{tabular}{c} PTSs, DSs, \\ Constructed \\ action \\ \end{tabular} & No & Linguistics \\
[38] BSLCP & 249 & 180 & Natural & English & PTSs, DSs, \\
[39] DGS Korpus & 330 & 50–300 & Natural & Ger./Eng. & Mouthing & No & Linguistics \\
[40] LSFB Corpus & 100 & 150 & Natural & French & DSs & No & Linguistics \\
[42] Corpus NGT & 92 & 72 & Natural & Dutch & DSs, Mouthing & No & Linguistics \\ \hline
[8] **Dicta-Sign-LSF-v2** & 16 & 11 & Natural & French & PTSs, DSs, FSs, \\  & 16 & 11 & Natural & French & FBuoys, NSs, Gs & Yes &
\begin{tabular}{c} SLR \& \\ linguistics \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table}
Table 2: Continuous Sign Language datasets. The top corpora have been developed and used by the SLR community, but they are either artificial or not representative of natural Sign Language. Others have been built by linguists, with natural discourse and detailed annotation, although they are not always consistent. To the best of our knowledge, Dicta-Sign–LSF–v2 and NCSLGR are the only two corpora built by linguists that have been used for _beyond gloss-level_ CSLR experiments.  
On the other hand, NCSLGR has consistent annotation across the corpus. However, this is not a dialogue corpus. Most utterances are artificial, furthermore the size of the corpus is small, with only two hours of recordings.