Text-dependent Forensic Voice Comparison: Likelihood Ratio Estimation with the Hidden Markov Model (HMM) and Gaussian Mixture Model – Universal Background Model (GMMUBM) Approaches

Among the more typical forensic voice comparison (FVC) approaches, the acoustic-phonetic statistical approach is suitable for text-dependent FVC, but it does not fully exploit available time-varying information of speech in its modelling. The automatic approach, on the other hand, essentially deals with text-independent cases, which means temporal information is not explicitly incorporated in the modelling. Text-dependent likelihood ratio (LR)-based FVC studies, in particular those that adopt the automatic approach, are few. This preliminary LR-based FVC study compares two statistical models, the Hidden Markov Model (HMM) and the Gaussian Mixture Model (GMM), for the calculation of forensic LRs using the same speech data. FVC experiments were carried out using different lengths of Japanese short words under a forensically realistic, but challenging condition: only two speech tokens for model training and LR estimation. Log-likelihood-ratio cost (Cllr) was used as the assessment metric. The study demonstrates that the HMM system constantly outperforms the GMM system in terms of average Cllr values. However, words longer than three mora are needed if the advantage of the HMM is to become evident. With a seven-mora word, for example, the HMM outperformed the GMM by a Cllr value of 0.073

ハミング ニヨル ケンサク キノウ オ ソナエタ オンガク ハイシン システム ノ カイハツ

Music retrieval systems are extremely useful for collecting digital music data from on-line music distribution sites. Especially, there is a great need to develop effective techniques for content-based music retrieval systems, which can retrieve by humming query. The main issues in this research is how to decide the similarity of each music features extracted from music data. In order to calculate the similarity, some conventional methods use Euclid distance or DP matching, but it is very hard to solve the problem of the vagueness of humming query. In this paper, we propose a new similar music retrieval method based on humming query using the Earth Mover's Distance as the distance measure. Computing the EMD is based on a solution to the transportation problem, and the EMD is applied as the distance measure on similar image retrieval systems. In addition, we focus that the time complexity of the EMD is exponential worst case toward the number of notes, the improved method to decrease the number of notes in the music feature is also proposed. Experimental results show that the proposed method can improve the retrieval precision of conventional systems

サフィックス アレイ ニ モトズク ゲンゴ モデル オ モチイタ オンセイ ニンシキ ニ カンスル ケンキュウ

For obtaining high speech recognition performance, we need high quality acoustic model and language model of speech recognition. In this study, we focus on the language model. The conventional language models, which are CFG, N-gram model, and so on, have some problems which are outputted the non-language characters and words sequence. Therefore, in this paper, we proposed the language model which was used the suffix array for speech recognition. The suffix array was proposed for the information retrieval. The advantages of the suffix array were that “予測可能” “無駄な仮説が生成さ れない” For evaluating the proposed language model, we conducted the similarly music information retrieval experiment using MIDI database. The experimental results showed that the proposed method was useful for the music information retrieval

トウケイテキ シュホウ オ モチイタ オンセイ シンゴウ ノ フクゲン シュホウ ノ カイリョウ

In recent years, IP telephone use has spread rapidly thanks to the development of VoIP (Voice over IP) technology. However, an unavoidable problem of the IP telephone is deterioration of speech due to packet loss, which often occurs on the wireless network. To overcome this problem, we propose a novel packet loss concealment algorithm using speech recognition and synthesis. This proposed method uses linguistic information and can deal with the lack of syllable units which conventional methods are unable to handle. We conducted subjective and objective evaluation experiments. These results showed the effectiveness of the proposed method. Although there is a processing delay in the proposed method, we believe that this method will open up new applications for speech recognition and speech synthesis technology

Squamous Cell Carcinoma of the Scalp after Artificial Hair Implantation

A 48-year-old man with a protruding tumor on the parietal region had undergone treatment of alopecia using artificial synthetic fibers 2 or 3 times a year for 10 years from 30 to 39 years old. Three months before the first consultation at our hospital, he noticed a small tumor that had gradually shown bleeding and discharge, with expansion of the affected area. A diagnosis of squamous cell carcinoma (SCC) was made based on a biopsy, and we resected the tumor with a 1-cm surgical margin from the reddened area around the protruding tumor (14 × 11 cm), including the periosteum membrane. No tight adhesion was found between the periosteum and skull, so we excised the outer table of the skull of the central part (diameter: 8 cm) for a pathological analysis. A pathological study showed moderately differentiated SCC with a negative surgical margin. The whole tumor was surrounded by scar tissue with buried artificial hair implants. The second surgery was performed on the 15th postoperative day. An anterolateral thigh flap was divided into 2 flaps to fit the circle-shaped wound. This is the second report of SCC developing after artificial hair implantation in the frontal-parietal scalp. The whole protruding tumor was surrounded by scar tissue with buried artificial hair implants. Proving the direct causal relationship between inflammation of scar tissue and SCC generation is difficult; however, our pathological findings support the possibility of the harmful effects of artificial hair implants