Mobile device vendors develop their customized Android OS (termed downstream) based on Google Android (termed upstream) to support new features. During daily independent development, the downstream also periodically merges changes of a new release from the upstream into its development branches, keeping in sync with the upstream. Due to a large number of commits to be merged, heavy code conflicts would be reported if auto-merge operations failed. Prior work has studied conflicts in this scenario. However, it is still unclear about the coupling between the downstream and the upstream (We term this coupling as the dependency facade), as well as how merge conflicts are related to this coupling. To address this issue, we first propose the DepFCD to reveal the dependency facade from three aspects, including interface-level dependencies that indicate a clear design boundary, intrusion-level dependencies which blur the boundary, and dependency constraints imposed by the upstream non-SDK restrictions. We then empirically investigate these three aspects (RQ1, RQ2, RQ3) and merge conflicts (RQ4) on the dependency facade. To support the study, we collect four open-source downstream projects and one industrial project, with 15 downstream and 15 corresponding upstream versions. Our study reveals interesting observations and suggests earlier mitigation of merge conflicts through a well-managed dependency facade. Our study will benefit the research about the coupling between upstream and downstream as well as the downstream maintenance practice.

Text normalization is an important component in text-to-speech system and the difficulty in text normalization is to disambiguate the non-standard words (NSWs). This paper develops a taxonomy of NSWs on the basis of a large scale Chinese corpus, and proposes a two-stage NSWs disambiguation strategy, finite state automata (FSA) for initial classification and maximum entropy (ME) classifiers for subclass disambiguation. Based on the above NSWs taxonomy, the two-stage approach achieves an F-score of 98.53% in open test, 5.23% higher than that of FSA based approach. Experiments show that the NSWs taxonomy ensures FSA a high baseline performance and ME classifiers make considerable improvement, and the two-stage approach adapts well to new domains.

Grapheme-to-phoneme (G2P) conversion is an important component in TTS systems. The difficulty in Chinese G2P conversion is to disambiguate the polyphones. In this paper, we formulate the polyphone disambiguation problem into a classification problem and propose a language independent classifier based on maximum entropy to address the issue. Furthermore, we introduce inequality smoothing to alleviate data sparseness and exploit language independent character features as linguistic knowledge. Experimental results show that the character features perform as well as the language dependent features such as words and part-of-speech, compared with the widely-used Gaussian smoothing, the inequality smoothing can greatly reduce the active features used in the classifier and achieve better performance. Our classifier achieves 96.35% in term of overall accuracy, greatly superior to 81.22% by using high-frequent "pin-yin"(Romanization of Chinese phoneme). Finally, we explore to merge all key polyphones into 6 groups and find that the overall accuracy only decreases about 2% and the active features are reduced more than 33% further.

In speech synthesis systems based on wave concatenation, us-ing longer units can generate more natural synthetic speech. In order to improve the usage of longer units in the corpus, this paper proposed a hierarchical non-uniform unit selection frame-work. Each layer included in the framework is an independent searching procedure which searches for different sized units and adopts suitable naturalness measuring functions related to the unit type. We have applied it to our Mandarin speech synthesis system according to the Chinese prosodic structure with respect to the statistical result in our corpus. Experiment result shows it outperforms our previous system. Index Terms: speech synthesis, unit selection, non-uniform, prosodic structure