Update documentation

Author: mdhk

_sources/index.md

@@ -40,7 +40,7 @@ We will present our tutorial about _Interpretability Techniques for Speech Model
 
 **Feature Importance Scoring methods**: 
 - Context-mixing: Attention{cite}`yangUnderstandingSelfAttentionSelfSupervised2020a,shimUNDERSTANDINGROLESELF2022,alastrueyLocalityAttentionDirect2022,audhkhasiAnalysisSelfAttentionHead2022`, Attention Norm{cite}`kobayashiAttentionNotOnly2020a`, Value-Zeroing {cite}`mohebbiHomophoneDisambiguationReveals2023a`
-- Feature attribution {cite}`fucciExplainabilitySpeechModels2024,shenReliabilityFeatureAttribution2025` (Gradient-based {cite}`prasadHowAccentsConfound2020,guptaPhonemeDiscretizedSaliency2024` & Perturbation-based {cite}`wuExplanationsforASR2023,pastor-etal-2024-explaining`
+- Feature attribution {cite}`fucciExplainabilitySpeechModels2024,shenReliabilityFeatureAttribution2025`: Gradient-based{cite}`prasadHowAccentsConfound2020,guptaPhonemeDiscretizedSaliency2024` & Perturbation-based{cite}`wuExplanationsforASR2023,pastor-etal-2024-explaining`
 
 ## References
 

index.html

@@ -673,7 +673,9 @@ <h2>Tutorial contents<a class="headerlink" href="#tutorial-contents"
                     <li>
                       <p>Context-mixing: Attention<span id="id7"><sup><a class="reference internal" href="#id36"
                               title="Shu-wen Yang, Andy T. Liu, and Hung-yi Lee. Understanding Self-Attention of Self-Supervised Audio Transformers. August 2020. URL: http://arxiv.org/abs/2006.03265 (visited on 2025-08-15), doi:10.48550/arXiv.2006.03265.">16</a>,<a
-                              class="reference internal" href="#id37">17</a>,<a class="reference internal" href="#id38"
+                              class="reference internal" href="#id37"
+                              title="Kyuhong Shim, Jungwook Choi, and Wonyong Sung. Understanding the role of self-attention for speech understanding. In International Conference on Learning Representations. 2022. URL: https://openreview.net/forum?id=AvcfxqRy4Y.">17</a>,<a
+                              class="reference internal" href="#id38"
                               title="Belen Alastruey, Javier Ferrando, Gerard I. Gállego, and Marta R. Costa-jussà. On the Locality of Attention in Direct Speech Translation. In Samuel Louvan, Andrea Madotto, and Brielen Madureira, editors, Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, 402–412. Dublin, Ireland, 2022. Association for Computational Linguistics. URL: https://aclanthology.org/2022.acl-srw.32/, doi:10.18653/v1/2022.acl-srw.32.">18</a>,<a
                               class="reference internal" href="#id39"
                               title="Kartik Audhkhasi, Yinghui Huang, Bhuvana Ramabhadran, and Pedro J. Moreno. Analysis of Self-Attention Head Diversity for Conformer-based Automatic Speech Recognition. 2022. URL: http://arxiv.org/abs/2209.06096, doi:10.48550/arXiv.2209.06096.">19</a></sup></span>,
@@ -687,12 +689,12 @@ <h2>Tutorial contents<a class="headerlink" href="#tutorial-contents"
                       <p>Feature attribution <span id="id10"><sup><a class="reference internal" href="#id30"
                               title="Dennis Fucci, Beatrice Savoldi, Marco Gaido, Matteo Negri, Mauro Cettolo, and Luisa Bentivogli. Explainability for Speech Models: On the Challenges of Acoustic Feature Selection. In Felice Dell'Orletta, Alessandro Lenci, Simonetta Montemagni, and Rachele Sprugnoli, editors, Proceedings of the 10th Italian Conference on Computational Linguistics (CLiC-it 2024), 373–381. Pisa, Italy, December 2024. CEUR Workshop Proceedings.">22</a>,<a
                               class="reference internal" href="#id31"
-                              title="Gaofei Shen, Hosein Mohebbi, Arianna Bisazza, Afra Alishahi, and Grzegorz Chrupała. On the reliability of feature attribution methods for speech classification. In Interspeech 2025. 2025. doi:10.48550/arXiv.2505.16406.">23</a></sup></span>
-                        (Gradient-based <span id="id11"><sup><a class="reference internal" href="#id32"
+                              title="Gaofei Shen, Hosein Mohebbi, Arianna Bisazza, Afra Alishahi, and Grzegorz Chrupała. On the reliability of feature attribution methods for speech classification. In Interspeech 2025. 2025. doi:10.48550/arXiv.2505.16406.">23</a></sup></span>:
+                        Gradient-based<span id="id11"><sup><a class="reference internal" href="#id32"
                               title="Archiki Prasad and Preethi Jyothi. How Accents Confound: Probing for Accent Information in End-to-End Speech Recognition Systems. In Dan Jurafsky, Joyce Chai, Natalie Schluter, and Joel Tetreault, editors, Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 3739–3753. Online, July 2020. Association for Computational Linguistics. URL: https://aclanthology.org/2020.acl-main.345 (visited on 2024-10-10), doi:10.18653/v1/2020.acl-main.345.">24</a>,<a
                               class="reference internal" href="#id33"
                               title="Shubham Gupta, Mirco Ravanelli, Pascal Germain, and Cem Subakan. Phoneme Discretized Saliency Maps for Explainable Detection of AI-Generated Voice. In Interspeech 2024, 3295–3299. 2024. doi:10.21437/Interspeech.2024-632.">25</a></sup></span>
-                        &amp; Perturbation-based <span id="id12"><sup><a class="reference internal" href="#id34"
+                        &amp; Perturbation-based<span id="id12"><sup><a class="reference internal" href="#id34"
                               title="Xiaoliang Wu, Peter Bell, and Ajitha Rajan. Explanations for automatic speech recognition. In ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), volume, 1-5. 2023. doi:10.1109/ICASSP49357.2023.10094635.">26</a>,<a
                               class="reference internal" href="#id35"
                               title="Eliana Pastor, Alkis Koudounas, Giuseppe Attanasio, Dirk Hovy, and Elena Baralis. Explaining speech classification models via word-level audio segments and paralinguistic features. In Yvette Graham and Matthew Purver, editors, Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers), 2221–2238. St. Julian's, Malta, March 2024. Association for Computational Linguistics. URL: https://aclanthology.org/2024.eacl-long.136/.">27</a></sup></span>
@@ -859,7 +861,11 @@ <h2>References<a class="headerlink" href="#references" title="Link to this headi
                     <div class="citation" id="id37" role="doc-biblioentry">
                       <span class="label"><span class="fn-bracket">[</span><a role="doc-backlink"
                           href="#id7">17</a><span class="fn-bracket">]</span></span>
-                      <p><strong>missing journal in shimUNDERSTANDINGROLESELF2022</strong></p>
+                      <p>Kyuhong Shim, Jungwook Choi, and Wonyong Sung. Understanding the role of self-attention for
+                        speech understanding. In <em>International Conference on Learning Representations</em>. 2022.
+                        URL: <a class="reference external"
+                          href="https://openreview.net/forum?id=AvcfxqRy4Y">https://openreview.net/forum?id=AvcfxqRy4Y</a>.
+                      </p>
                     </div>
                     <div class="citation" id="id38" role="doc-biblioentry">
                       <span class="label"><span class="fn-bracket">[</span><a role="doc-backlink"