Pop Music Highlighter: Marking the Emotion Keypoints

The goal of music highlight extraction is to get a short consecutive segment of a piece of music that provides an effective representation of the whole piece. In a previous work, we introduced an attention-based convolutional recurrent neural network that uses music emotion classification as a surrogate task for music highlight extraction, for Pop songs. The rationale behind that approach is that the highlight of a song is usually the most emotional part. This paper extends our previous work in the following two aspects. First, methodology-wise we experiment with a new architecture that does not need any recurrent layers, making the training process faster. Moreover, we compare a late-fusion variant and an early-fusion variant to study which one better exploits the attention mechanism. Second, we conduct and report an extensive set of experiments comparing the proposed attention-based methods against a heuristic energy-based method, a structural repetition-based method, and a few other simple feature-based methods for this task. Due to the lack of public-domain labeled data for highlight extraction, following our previous work we use the RWC POP 100-song data set to evaluate how the detected highlights overlap with any chorus sections of the songs. The experiments demonstrate the effectiveness of our methods over competing methods. For reproducibility, we open source the code and pre-trained model at https://github.com/remyhuang/pop-music-highlighter/.Comment: Transactions of the ISMIR vol. 1, no.

Revisiting the problem of audio-based hit song prediction using convolutional neural networks

Being able to predict whether a song can be a hit has impor- tant applications in the music industry. Although it is true that the popularity of a song can be greatly affected by exter- nal factors such as social and commercial influences, to which degree audio features computed from musical signals (whom we regard as internal factors) can predict song popularity is an interesting research question on its own. Motivated by the recent success of deep learning techniques, we attempt to ex- tend previous work on hit song prediction by jointly learning the audio features and prediction models using deep learning. Specifically, we experiment with a convolutional neural net- work model that takes the primitive mel-spectrogram as the input for feature learning, a more advanced JYnet model that uses an external song dataset for supervised pre-training and auto-tagging, and the combination of these two models. We also consider the inception model to characterize audio infor- mation in different scales. Our experiments suggest that deep structures are indeed more accurate than shallow structures in predicting the popularity of either Chinese or Western Pop songs in Taiwan. We also use the tags predicted by JYnet to gain insights into the result of different models.Comment: To appear in the proceedings of 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP

Understand the customer experience of luxury brands at before purchase stage and investigate the way to enhance this experience.

The importance of customer experience is enhancing significantly, especially on luxury brand. Customer experiences can be discussed from the decision making process model. In this paper, it will focus on luxury brands and investigate relative attributes which will influence customer experience at the before purchase stage. There are some elements like personal attributes and environmental atmosphere. The information from 2 focus groups was used for data analysis in the paper. The results indicate that these elements can have lead to customer experiences. Furthermore, focus group interview findings show that five store factors including layout, general interior, innovation, product display and signs and human variables have positive effect on consumer experience of luxury brand at the before purchase stage. On the other hand, personal attributes show that goal, memory, involvement and attitude also contribute to increase customer experiences. This paper also mentioned about managerial implication, research limitation, and provided suggestions for further research

Is clopidogrel better than aspirin following breakthrough strokes while on aspirin? A retrospective cohort study.

ObjectiveThere is insufficient evidence on which to base a recommendation for optimal antiplatelet therapy following a stroke while on aspirin. The objective was to compare clopidogrel initiation vs aspirin reinitiation for vascular risk reduction among patients with ischaemic stroke on aspirin at the time of their index stroke.DesignRetrospective.SettingWe conducted a nationwide cohort study by retrieving all hospitalised patients (≥18 years) with a primary diagnosis of ischaemic stroke between 2003 and 2009 from Taiwan National Health Insurance Research Database.ParticipantsAmong 3862 patients receiving aspirin before the index ischaemic stroke and receiving either aspirin or clopidogrel after index stroke during follow-up period, 1623 were excluded due to a medication possession ratio <80%. Also, 355 were excluded due to history of atrial fibrillation, valvular heart disease or coagulopathy. Therefore, 1884 patients were included in our final analysis.InterventionsPatients were categorised into two groups based on whether clopidogrel or aspirin was prescribed during the follow-up period. Follow-up was from time of the index stroke to admission for recurrent stroke or myocardial infarction, death or the end of 2010.Primary and secondary outcome measuresThe primary end point was hospitalisation due to a new-onset major adverse cardiovascular event (MACE: composite of any stroke or myocardial infarction). The leading secondary end point was any recurrent stroke.ResultsCompared to aspirin, clopidogrel was associated with a lower occurrence of future MACE (HR=0.54, 95% CI 0.43 to 0.68, p<0.001, number needed to treat: 8) and recurrent stroke (HR=0.54, 95% CI 0.42 to 0.69, p<0.001, number needed to treat: 9) after adjustment of relevant covariates.ConclusionsAmong patients with an ischaemic stroke while taking aspirin, clopidogrel initiation was associated with fewer recurrent vascular events than aspirin reinitiation