In this task, you will be presented with a context from an academic paper and a question separated with a 
. You have to answer the question based on the context.

Input: Consider Input: Results show that the CJFA encoder obtains significantly better phone classification accuracy than the VAE baseline and also than the CJFS encoder. These results are replicated for speaker recognition tasks. 
 Question: Which approach out of two proposed in the paper performed better in experiments?

Output: CJFA encoder 


Input: Consider Input: Our experiments are run using the English$\rightarrow $Italian/German portions of the MuST-C corpus BIBREF25, which is extracted from TED talks, using the same train/validation/test split as provided with the corpus (see Table TABREF18). As additional data, we use a mix of public and proprietary data for about 16 million sentence pairs for English-Italian (En-It) and $4.4$ million WMT14 sentence pairs for the English-German (En-De). 
 Question: What dataset do they use?

Output: English$\rightarrow $Italian/German portions of the MuST-C corpus As additional data, we use a mix of public and proprietary data for about 16 million sentence pairs for English-Italian (En-It) and $4.4$ million WMT14 sentence pairs for the English-German (En-De)


Input: Consider Input: We use the Ultrax Typically Developing dataset (UXTD) from the publicly available UltraSuite repository BIBREF19 . This dataset contains synchronized acoustic and ultrasound data from 58 typically developing children, aged 5-12 years old (31 female, 27 male). The data was aligned at the phone-level, according to the methods described in BIBREF19 , BIBREF25 . The data was recorded using an Ultrasonix SonixRP machine using Articulate Assistant Advanced (AAA) software at INLINEFORM0 121fps with a 135 field of view. A single ultrasound frame consists of 412 echo returns from each of the 63 scan lines (63x412 raw frames). 
 Question: What are the characteristics of the dataset?


Output: synchronized acoustic and ultrasound data from 58 typically developing children, aged 5-12 years old (31 female, 27 male) data was aligned at the phone-level 121fps with a 135 field of view single ultrasound frame consists of 412 echo returns from each of the 63 scan lines (63x412 raw frames)